1
00:00:09,880 --> 00:00:13,399
Speaker 1: Helen Baker. Welcome to the mentor absolute privileged to be here.

2
00:00:13,560 --> 00:00:15,080
Speaker 1: I want to talk a little bit about it because

3
00:00:15,080 --> 00:00:19,000
Speaker 1: you've got a pretty amazing backstory, Helen Baker, And I

4
00:00:19,520 --> 00:00:21,280
Speaker 1: want to look at you. Unless you're married to a Baker,

5
00:00:22,079 --> 00:00:24,079
Speaker 1: and even if you're not married to a person called

6
00:00:24,079 --> 00:00:28,040
Speaker 1: Baker or your first name Helen, you're of Asian descend

7
00:00:28,080 --> 00:00:30,840
Speaker 1: by the look of things. Where were you born?

8
00:00:31,160 --> 00:00:34,120
Speaker 2: So? I was born in the Philippines in a city

9
00:00:34,120 --> 00:00:36,800
Speaker 2: called the College, which is south of Manila.

10
00:00:36,800 --> 00:00:40,720
Speaker 1: Right and big joint. So tell me the story, Like,

11
00:00:40,800 --> 00:00:42,280
Speaker 1: how did you end up here in Australia.

12
00:00:42,400 --> 00:00:47,120
Speaker 2: Yeah, so I was orphaned when I was a.

13
00:00:47,040 --> 00:00:49,320
Speaker 1: Baby, which means you went to an orphanage. I presume

14
00:00:49,360 --> 00:00:51,800
Speaker 1: that's which you mean. Yeah, yeah, parents.

15
00:00:52,120 --> 00:00:54,680
Speaker 2: So I was given up for adoption. And the reason

16
00:00:54,720 --> 00:00:56,560
Speaker 2: I was given up was because my mother was dying

17
00:00:56,560 --> 00:00:59,960
Speaker 2: at the time. Oh wow, yeah, father couldn't afford to keep.

18
00:00:59,840 --> 00:01:03,640
Speaker 1: Me sad Like, what was she older or younger?

19
00:01:04,480 --> 00:01:07,360
Speaker 2: I don't know, you don't know, I don't know the backstory.

20
00:01:07,920 --> 00:01:09,040
Speaker 1: But how do you know she was dying?

21
00:01:09,280 --> 00:01:15,720
Speaker 2: Well, the nursery kept records of the orphans, right, and

22
00:01:15,840 --> 00:01:18,280
Speaker 2: they told my adoptive parents that the reason I was

23
00:01:18,280 --> 00:01:20,520
Speaker 2: given up was because she was dying at the time.

24
00:01:21,600 --> 00:01:25,160
Speaker 2: And yeah, my father was a cane field worker, couldn't

25
00:01:25,160 --> 00:01:27,360
Speaker 2: afford to keep me and two of my siblings had

26
00:01:27,360 --> 00:01:30,479
Speaker 2: passed away from malnutrition. So I was one of ten

27
00:01:30,600 --> 00:01:34,319
Speaker 2: children whoah from one mother, from one.

28
00:01:34,240 --> 00:01:38,800
Speaker 1: Mother whoa yeah one as she wasn't well like ten kids. No,

29
00:01:38,880 --> 00:01:41,800
Speaker 1: I don't mean flippantly like that's a heavy load. It

30
00:01:41,880 --> 00:01:45,959
Speaker 1: is heavy on anybody. If you're genetically any way related

31
00:01:45,959 --> 00:01:48,240
Speaker 1: to mom, wouldn't have been a too big a person,

32
00:01:48,400 --> 00:01:51,160
Speaker 1: particularly during that period growing up in the Philippines in

33
00:01:51,200 --> 00:01:51,880
Speaker 1: a poor area.

34
00:01:52,000 --> 00:01:52,800
Speaker 2: Yeah, well that's right.

35
00:01:54,400 --> 00:01:59,480
Speaker 1: And do you ever think to yourself in biologically that

36
00:01:59,520 --> 00:02:00,640
Speaker 1: you'd like to meet your father?

37
00:02:01,320 --> 00:02:02,000
Speaker 2: Yeah?

38
00:02:02,200 --> 00:02:05,160
Speaker 1: Have you met him? No, he's alive.

39
00:02:06,240 --> 00:02:08,880
Speaker 2: I have absolutely no idea. And I did start that

40
00:02:09,040 --> 00:02:13,680
Speaker 2: search some time ago, but they actually shut down the department. Wow,

41
00:02:13,800 --> 00:02:17,560
Speaker 2: the government department that organized all of those searches. But

42
00:02:18,840 --> 00:02:21,400
Speaker 2: when I was younger, my parents always asked me, do

43
00:02:21,480 --> 00:02:23,720
Speaker 2: I want to go back to the Philippines?

44
00:02:23,919 --> 00:02:26,720
Speaker 1: How old? How old were you when you adopted? In

45
00:02:26,760 --> 00:02:28,400
Speaker 1: other words, did you live thirteen months?

46
00:02:28,680 --> 00:02:28,800
Speaker 2: Oh?

47
00:02:28,840 --> 00:02:30,840
Speaker 1: Okay, so you wouldn't have any memory of the place.

48
00:02:31,560 --> 00:02:36,360
Speaker 1: And so I guess your adopted parents, mom and dad

49
00:02:36,840 --> 00:02:40,639
Speaker 1: have told you the story about what they saw when

50
00:02:40,639 --> 00:02:43,280
Speaker 1: they went down went to the particular orphanage. I mean,

51
00:02:43,320 --> 00:02:45,680
Speaker 1: how's it all work? Because I'm always been I mystified

52
00:02:45,760 --> 00:02:48,800
Speaker 1: how this stuff works, Like how does Australian couple, I

53
00:02:48,840 --> 00:02:53,520
Speaker 1: presume the Bakers they've decided We'll talk about them in

54
00:02:53,520 --> 00:02:55,200
Speaker 1: a moment, but they've decided to go to the Philippines

55
00:02:55,240 --> 00:02:56,480
Speaker 1: to adopt a kid. Does that it works where you

56
00:02:56,600 --> 00:03:00,320
Speaker 1: make an application near the Philippines embassy. What's yeah?

57
00:03:00,400 --> 00:03:02,920
Speaker 2: Yeah, so back then, this is in the seventies, so

58
00:03:03,000 --> 00:03:08,960
Speaker 2: I am actually older than I look. So yeah, so

59
00:03:09,040 --> 00:03:11,080
Speaker 2: back in the seventies it was actually a lot easier

60
00:03:11,120 --> 00:03:14,280
Speaker 2: to adopt than it is now. And they did it

61
00:03:14,320 --> 00:03:22,760
Speaker 2: through an organization called Asian And how they did it

62
00:03:22,840 --> 00:03:27,440
Speaker 2: was they literally wrote to the orphanage and lots of

63
00:03:27,480 --> 00:03:29,480
Speaker 2: back and forth. Back then it was paper. Everything was

64
00:03:29,480 --> 00:03:31,680
Speaker 2: paper based, so it took a year for the adoption

65
00:03:31,760 --> 00:03:34,720
Speaker 2: to come through. But my dad was also working over

66
00:03:34,800 --> 00:03:38,520
Speaker 2: in the Philippines with Apex. Do you remember Apex like

67
00:03:38,720 --> 00:03:41,160
Speaker 2: Rotary And he was working on a project over in

68
00:03:41,200 --> 00:03:46,800
Speaker 2: the Philippines Rebuilding Orphanages project. Yeah, yeah, correct, and then

69
00:03:46,960 --> 00:03:51,960
Speaker 2: he he saw the devastation of you know, these children,

70
00:03:52,040 --> 00:03:54,680
Speaker 2: what it was like in the orphanages, and then wrote

71
00:03:54,720 --> 00:03:57,360
Speaker 2: back to my mum and said, can we adopt one

72
00:03:57,400 --> 00:03:58,560
Speaker 2: of these children? Oh?

73
00:03:58,600 --> 00:04:00,440
Speaker 1: That's cool? Did they have Do they have kids of

74
00:04:00,520 --> 00:04:01,240
Speaker 1: their own at the time?

75
00:04:02,000 --> 00:04:04,320
Speaker 2: Yes, So I've got an older brother and an older

76
00:04:04,360 --> 00:04:06,000
Speaker 2: sister who looks nothing like me.

77
00:04:06,240 --> 00:04:08,680
Speaker 1: Yeah, I can imagine if they were born to miss

78
00:04:08,720 --> 00:04:13,720
Speaker 1: from Missus Baker exactly in Australia. And so your father

79
00:04:13,920 --> 00:04:15,840
Speaker 1: and it was sort of like your father's idea as

80
00:04:15,840 --> 00:04:20,000
Speaker 1: a result of seeing the conditions that orphans have lived

81
00:04:20,080 --> 00:04:23,200
Speaker 1: under in these environments. And how does that make you

82
00:04:23,240 --> 00:04:25,360
Speaker 1: feel when you hear that story? I mean, and by

83
00:04:25,400 --> 00:04:26,960
Speaker 1: the way, when did they first tell you that story?

84
00:04:27,320 --> 00:04:28,360
Speaker 1: I mean we were a little kid, boy.

85
00:04:28,400 --> 00:04:30,920
Speaker 2: I think I always knew. I mean I was very

86
00:04:30,920 --> 00:04:32,400
Speaker 2: different and I was.

87
00:04:33,400 --> 00:04:35,960
Speaker 1: You knew, but you hadn't been told. How does it work?

88
00:04:36,000 --> 00:04:38,000
Speaker 2: I mean I must have been told when I was

89
00:04:38,240 --> 00:04:40,359
Speaker 2: from a young age. I mean I don't remember the

90
00:04:40,400 --> 00:04:43,240
Speaker 2: specific day when Mum and Dad sat me down and said,

91
00:04:43,240 --> 00:04:44,800
Speaker 2: by the way, you adopted. I think it was just

92
00:04:44,880 --> 00:04:47,840
Speaker 2: always it was they must have told me from a

93
00:04:47,920 --> 00:04:49,880
Speaker 2: very young age, and I always new but it was

94
00:04:49,960 --> 00:04:52,040
Speaker 2: very obvious because I was the youngly Asian in school.

95
00:04:52,400 --> 00:04:53,760
Speaker 1: Yes, well the only Asian.

96
00:04:53,960 --> 00:04:55,720
Speaker 2: Well. I was plucked out of this orphanage and then

97
00:04:55,720 --> 00:05:00,280
Speaker 2: placed into a rural farming community land. Yeah, up in

98
00:05:00,720 --> 00:05:04,680
Speaker 2: warrigal And, Gippsland. And back then it was yeah, I

99
00:05:04,720 --> 00:05:08,680
Speaker 2: was the only Asian in school. And how was that terrible?

100
00:05:09,040 --> 00:05:10,440
Speaker 1: We're going back into the seven.

101
00:05:10,240 --> 00:05:12,080
Speaker 2: We going back to seventy years and just bear in

102
00:05:12,120 --> 00:05:15,599
Speaker 2: mind as well that it was shortly after the White

103
00:05:15,600 --> 00:05:19,760
Speaker 2: Australian Policy had been abolished, especially two years after, so.

104
00:05:20,080 --> 00:05:24,720
Speaker 1: We forget about the White Australian policy too. Racism was rife, yes,

105
00:05:24,960 --> 00:05:26,320
Speaker 1: probably more so in the regionally.

106
00:05:26,400 --> 00:05:28,560
Speaker 2: In the regional areas it was rife. I mean I

107
00:05:28,600 --> 00:05:30,560
Speaker 2: was spat on in the street, really told to go

108
00:05:30,600 --> 00:05:32,480
Speaker 2: back to where I came from. I was the only

109
00:05:32,520 --> 00:05:33,480
Speaker 2: Asian in my school.

110
00:05:34,160 --> 00:05:36,159
Speaker 1: It was because Vietnam was on at the time too,

111
00:05:36,480 --> 00:05:38,360
Speaker 1: so a lot of Australians would have been filthy on that,

112
00:05:38,720 --> 00:05:40,800
Speaker 1: on someone who might look like their.

113
00:05:40,760 --> 00:05:44,599
Speaker 2: Vietnamese everyone and only then I don't think they could

114
00:05:44,640 --> 00:05:48,000
Speaker 2: really distinguish between the different countries as well.

115
00:05:48,720 --> 00:05:53,400
Speaker 1: Totally they were particular. Exactly kid from a kid, Yeah, exactly,

116
00:05:53,440 --> 00:05:56,359
Speaker 1: Although you would, I'll guarantee you can pick the difference

117
00:05:56,360 --> 00:05:58,839
Speaker 1: between most of the Asian nations.

118
00:05:59,680 --> 00:06:02,800
Speaker 2: Yeah, I'd like to think that I'm pretty savvy about that,

119
00:06:03,120 --> 00:06:06,040
Speaker 2: But back then, kids particularly had no idea, So of

120
00:06:06,040 --> 00:06:08,919
Speaker 2: course I got called everything from people thought I was

121
00:06:08,960 --> 00:06:13,320
Speaker 2: Aboriginal through to Chinese, Japanese, you name it. I was

122
00:06:14,000 --> 00:06:15,600
Speaker 2: every possible thing.

123
00:06:15,720 --> 00:06:17,600
Speaker 1: What's that like for a kid? I mean, I grew

124
00:06:17,680 --> 00:06:20,920
Speaker 1: up in a certain part of Sydney where in those

125
00:06:21,000 --> 00:06:23,880
Speaker 1: days a lot of the kids who Australia like in

126
00:06:23,960 --> 00:06:28,919
Speaker 1: Irish English derivation, and I had Greek surname, Greek food,

127
00:06:29,160 --> 00:06:31,400
Speaker 1: you know, blah blah, different sort of things going on

128
00:06:31,480 --> 00:06:34,040
Speaker 1: in my life. And I experienced a bit of it,

129
00:06:34,120 --> 00:06:37,320
Speaker 1: not too much, but like enough to be aware of it.

130
00:06:37,760 --> 00:06:41,760
Speaker 1: But I can't imagine being, say, in your case, by

131
00:06:41,760 --> 00:06:44,240
Speaker 1: the way, i'd left score at that stage when you

132
00:06:44,279 --> 00:06:48,120
Speaker 1: were growing up. But I can't imagine being someone who

133
00:06:48,160 --> 00:06:52,760
Speaker 1: was fully Asian fully and Asians looked totally different to Europeans.

134
00:06:52,800 --> 00:06:55,200
Speaker 1: To Europeans sort of a little bit look like the

135
00:06:55,240 --> 00:06:58,320
Speaker 1: English and the Irish et cetera. Where difference is our

136
00:06:58,320 --> 00:07:01,560
Speaker 1: skin's a bit darker, and it is definitely different, but

137
00:07:01,680 --> 00:07:03,600
Speaker 1: you're you would have been completely different.

138
00:07:04,880 --> 00:07:07,560
Speaker 2: I stood out like I saw So how.

139
00:07:07,440 --> 00:07:09,560
Speaker 1: Did you feel at the time, I mean, do you

140
00:07:09,640 --> 00:07:12,640
Speaker 1: remember feelings of despair? Perhaps?

141
00:07:12,800 --> 00:07:18,360
Speaker 2: Oh well? And truly yeah, absolutely, no, I was. It

142
00:07:18,360 --> 00:07:20,800
Speaker 2: was such a double edged sword because I was incredibly

143
00:07:20,840 --> 00:07:23,240
Speaker 2: grateful for the opportunities that I had.

144
00:07:23,440 --> 00:07:25,040
Speaker 1: So you aware of gratefulness, You're aware of.

145
00:07:25,360 --> 00:07:29,760
Speaker 2: How you were for sure, absolutely. I mean it was

146
00:07:29,880 --> 00:07:35,200
Speaker 2: very obvious that I had come from dire circumstances, so

147
00:07:35,560 --> 00:07:39,960
Speaker 2: I was grateful that. And I think this was drummed

148
00:07:39,960 --> 00:07:41,520
Speaker 2: in to me from a young age from my dad

149
00:07:41,560 --> 00:07:44,680
Speaker 2: as well, that there's there's always someone worse out there

150
00:07:44,680 --> 00:07:47,760
Speaker 2: than yourself. I was pretty fortunate for me, That's the truth, absolutely,

151
00:07:48,360 --> 00:07:51,480
Speaker 2: But at the same time it was it was a

152
00:07:51,520 --> 00:07:55,400
Speaker 2: real struggle because I didn't know who I was, how

153
00:07:55,440 --> 00:07:58,040
Speaker 2: to fit in. I just wanted to be to be white,

154
00:07:58,080 --> 00:08:01,520
Speaker 2: to be honest, because I was just teased all the

155
00:08:01,600 --> 00:08:03,280
Speaker 2: time every day.

156
00:08:03,600 --> 00:08:05,080
Speaker 1: What do you think it is, Allen? Do you think

157
00:08:05,080 --> 00:08:08,160
Speaker 1: it's the color of your skin, or the style of

158
00:08:08,200 --> 00:08:10,600
Speaker 1: your hair, or the color of your eyes? What is

159
00:08:10,640 --> 00:08:12,880
Speaker 1: it that sort of was a thing that freaked people

160
00:08:12,920 --> 00:08:13,920
Speaker 1: out most.

161
00:08:15,200 --> 00:08:18,680
Speaker 2: I think it was color of skin. Yeah, yeah. And

162
00:08:18,760 --> 00:08:21,640
Speaker 2: I'll give you an example of something that was quite

163
00:08:21,680 --> 00:08:26,320
Speaker 2: devastating for me. When I was in high school. I

164
00:08:26,440 --> 00:08:29,720
Speaker 2: was the only actually there was one other Asian in

165
00:08:29,800 --> 00:08:32,199
Speaker 2: high school as well, and we both knew each other

166
00:08:32,240 --> 00:08:35,880
Speaker 2: and the struggles that we both faced. And there was

167
00:08:35,920 --> 00:08:40,440
Speaker 2: a school play that we auditioned for. And I remember

168
00:08:40,880 --> 00:08:43,400
Speaker 2: going along and auditioning for this school play, and you

169
00:08:43,440 --> 00:08:45,920
Speaker 2: don't have it back then. They put the paper up

170
00:08:45,960 --> 00:08:48,440
Speaker 2: on the board and you'd go afterwards and see whether

171
00:08:48,480 --> 00:08:51,640
Speaker 2: you got a parsh. And I went to see and

172
00:08:51,679 --> 00:08:53,520
Speaker 2: I got this part, and I thought, oh wow, it's

173
00:08:53,559 --> 00:08:57,400
Speaker 2: awesome this part in the school play. And then I

174
00:08:57,440 --> 00:09:01,040
Speaker 2: found out later that this other Asian also got a pash.

175
00:09:01,400 --> 00:09:04,640
Speaker 2: And we were both playing indigenous.

176
00:09:04,320 --> 00:09:09,640
Speaker 1: Kids, Australian indigenous kids, yes, as opposed to Filipino indigenous.

177
00:09:09,240 --> 00:09:12,679
Speaker 2: Kids, because just because we had brown skin. Wow. So

178
00:09:13,679 --> 00:09:17,040
Speaker 2: they decide that's just an example, one very small example.

179
00:09:16,720 --> 00:09:19,320
Speaker 1: And how did you did? We did your heart slump?

180
00:09:19,920 --> 00:09:20,440
Speaker 2: Of course?

181
00:09:21,120 --> 00:09:23,160
Speaker 1: Of course, I guess you're not going to get the

182
00:09:23,240 --> 00:09:26,520
Speaker 1: nativities seen as Mary at Christmas time or something like that.

183
00:09:27,880 --> 00:09:29,800
Speaker 1: But I'm just saying, like, you know, I don't know,

184
00:09:29,960 --> 00:09:31,920
Speaker 1: don't she could have been asing. I don't think she was.

185
00:09:32,440 --> 00:09:34,360
Speaker 1: But I mean, by you today, that wouldn't be the case.

186
00:09:34,520 --> 00:09:37,000
Speaker 1: You could get a Nativity scene Mary today because it

187
00:09:37,000 --> 00:09:39,560
Speaker 1: doesn't really matter because you're just you're just playing a

188
00:09:39,600 --> 00:09:41,360
Speaker 1: part as opposed to having too.

189
00:09:41,880 --> 00:09:46,480
Speaker 2: But back then it was because you've got brown skin,

190
00:09:46,600 --> 00:09:49,640
Speaker 2: therefore you should be in a in a role that

191
00:09:50,600 --> 00:09:52,319
Speaker 2: is aboriginal, according to them.

192
00:09:52,800 --> 00:09:54,200
Speaker 1: When I went to school, we had one kid in

193
00:09:54,200 --> 00:09:56,440
Speaker 1: the whole school who was Chinese kid. I member, your

194
00:09:56,520 --> 00:09:59,920
Speaker 1: name is Michael Chinui and god, who's an unbelievable athlete,

195
00:10:00,160 --> 00:10:02,439
Speaker 1: guy like he could do anything. He was a bit

196
00:10:02,480 --> 00:10:06,240
Speaker 1: younger than me. But it's funny, nobody my school is

197
00:10:06,240 --> 00:10:09,120
Speaker 1: such a mix of kids Lebanese, Greeks, Italians, and like

198
00:10:09,400 --> 00:10:13,160
Speaker 1: every mix you can imagine different regional areas, and you know,

199
00:10:13,160 --> 00:10:16,600
Speaker 1: because in the West and but this kid never had

200
00:10:16,600 --> 00:10:21,880
Speaker 1: a problem, like nobody really said much like said negative

201
00:10:21,880 --> 00:10:23,839
Speaker 1: things about him. I remember I held him in awe

202
00:10:23,840 --> 00:10:27,679
Speaker 1: because of this his unbelieved athleticism. Is an incredible, incredible

203
00:10:27,720 --> 00:10:32,760
Speaker 1: athlete he was, and racism sort of did exist I'm

204
00:10:32,760 --> 00:10:36,240
Speaker 1: going back, you know, ten years before you're talking about

205
00:10:36,640 --> 00:10:40,880
Speaker 1: in the sixties. I was at school sixties to late sixties.

206
00:10:40,920 --> 00:10:44,800
Speaker 1: I left school seventy three, so that was actually last

207
00:10:44,840 --> 00:10:47,280
Speaker 1: year was my fiftieth anniversary doing a year twelve. I

208
00:10:47,280 --> 00:10:50,360
Speaker 1: can't believe it can like fifty years animersal My god

209
00:10:50,480 --> 00:10:53,319
Speaker 1: only died when I realized and I went and saw

210
00:10:53,320 --> 00:10:55,960
Speaker 1: all my old schoolmates who were I was young for

211
00:10:56,040 --> 00:10:58,160
Speaker 1: my years and younger than all other kids. And I

212
00:10:58,240 --> 00:11:00,079
Speaker 1: got a shock when I wasn't seen he's got fifty

213
00:11:00,640 --> 00:11:02,240
Speaker 1: And I got a shock when I went and saw them.

214
00:11:02,880 --> 00:11:07,280
Speaker 1: But we But I didn't realize how very Australian my

215
00:11:07,400 --> 00:11:10,400
Speaker 1: school was until I saw these guys out at Rusby. Yeah,

216
00:11:10,679 --> 00:11:15,360
Speaker 1: and you're someone like you growing up in your area.

217
00:11:16,320 --> 00:11:17,960
Speaker 1: I know what it did to me being one of

218
00:11:17,960 --> 00:11:23,480
Speaker 1: the wogs. Was it actually made me try harder? Effect

219
00:11:23,840 --> 00:11:26,480
Speaker 1: did it have on you as a student.

220
00:11:28,720 --> 00:11:32,480
Speaker 2: As a student, No, it didn't. I was with the opposite.

221
00:11:32,640 --> 00:11:35,720
Speaker 2: I was quite rebellious, said fuck them, Yeah, I was

222
00:11:35,880 --> 00:11:37,800
Speaker 2: very What does that mean?

223
00:11:37,800 --> 00:11:40,760
Speaker 1: What did you to cut your hair gray, fingernails, your

224
00:11:40,800 --> 00:11:42,079
Speaker 1: hair purple and green?

225
00:11:42,080 --> 00:11:44,320
Speaker 2: I don't know, no, I just I think I acted

226
00:11:44,360 --> 00:11:47,600
Speaker 2: out just because well there are a lot of a

227
00:11:47,600 --> 00:11:50,400
Speaker 2: lot of reasons, but I think it stemmed from conversations

228
00:11:50,440 --> 00:11:51,920
Speaker 2: that I would have with my dad. So my dad

229
00:11:51,960 --> 00:11:54,120
Speaker 2: was very much my role model growing up, and he

230
00:11:55,120 --> 00:11:58,559
Speaker 2: would always say, don't give a shit about the color

231
00:11:58,559 --> 00:12:00,880
Speaker 2: of your skin, like, it's not about what you look like,

232
00:12:01,000 --> 00:12:06,200
Speaker 2: it's about what's inside that counts. So often, yeah, it

233
00:12:06,240 --> 00:12:10,560
Speaker 2: would just be a few kind of mentality. So yeah,

234
00:12:10,559 --> 00:12:14,760
Speaker 2: I was really I was really rebellious and did.

235
00:12:14,600 --> 00:12:16,400
Speaker 1: Lots of naughty things.

236
00:12:16,720 --> 00:12:19,040
Speaker 2: Yeah, lots of naughty things. I was naughty. I was

237
00:12:19,040 --> 00:12:19,560
Speaker 2: really naughty.

238
00:12:19,800 --> 00:12:22,480
Speaker 1: Naughty as a young girl or naughty as a teenager,

239
00:12:22,600 --> 00:12:24,760
Speaker 1: like naughty and like that.

240
00:12:24,840 --> 00:12:27,320
Speaker 2: Well no, I no, no, I didn't do no, not

241
00:12:27,320 --> 00:12:30,000
Speaker 2: that naughty. I didn't do drugs and all that kind

242
00:12:30,000 --> 00:12:31,960
Speaker 2: of stuff. But I was just I was rebellious in

243
00:12:32,000 --> 00:12:33,000
Speaker 2: a lot of a lot of.

244
00:12:32,960 --> 00:12:36,400
Speaker 1: Ways, just in being cheeking class.

245
00:12:36,000 --> 00:12:39,880
Speaker 2: Just being cheeky, doing things that pushed the boundaries a lot,

246
00:12:41,360 --> 00:12:43,079
Speaker 2: you know. I just I think I was a risk

247
00:12:43,120 --> 00:12:46,200
Speaker 2: taker as well. So I literally just I don't know,

248
00:12:46,640 --> 00:12:47,240
Speaker 2: I think.

249
00:12:47,200 --> 00:12:50,280
Speaker 1: Did you hang out with the bad kids? No, not really,

250
00:12:50,640 --> 00:12:53,760
Speaker 1: not as a lonely kid, like in terms of friends,

251
00:12:53,760 --> 00:12:55,160
Speaker 1: I was had.

252
00:12:55,040 --> 00:13:00,400
Speaker 2: One best friend, Tiffany. She was amazing and her family

253
00:13:00,440 --> 00:13:04,400
Speaker 2: were incredibly supportive of me. But yeah, I think I

254
00:13:04,440 --> 00:13:07,480
Speaker 2: was just I didn't know who I wanted to be.

255
00:13:07,559 --> 00:13:10,720
Speaker 2: I was very much you didn't become anywhere. Yeah, I

256
00:13:10,760 --> 00:13:13,679
Speaker 2: really lacked identity.

257
00:13:12,880 --> 00:13:14,880
Speaker 1: Because I'm sitting here talking to you, and obviously your

258
00:13:14,920 --> 00:13:18,120
Speaker 1: skin colors different anyone else in the room. There's one, two, three, four,

259
00:13:18,200 --> 00:13:20,800
Speaker 1: five or six people sitting in this room, and but

260
00:13:20,880 --> 00:13:23,280
Speaker 1: all different nationalities. But look at it to me, and

261
00:13:24,160 --> 00:13:30,600
Speaker 1: and and I guess like today all kids, I guess

262
00:13:30,640 --> 00:13:32,520
Speaker 1: like and me at the time, so we all want

263
00:13:32,559 --> 00:13:35,960
Speaker 1: to belong somewhere. But when you don't really know where

264
00:13:35,960 --> 00:13:37,599
Speaker 1: you belong, like I was a half cast because my

265
00:13:37,679 --> 00:13:40,280
Speaker 1: mum was Irish, but I was both like I didn't

266
00:13:40,280 --> 00:13:42,559
Speaker 1: know whether I belong on this side or the other side.

267
00:13:42,640 --> 00:13:44,640
Speaker 1: Like and it was a bit a little bit confusing

268
00:13:44,679 --> 00:13:47,280
Speaker 1: to me. You know, obviously okay with it these days

269
00:13:47,280 --> 00:13:50,880
Speaker 1: because normal, but with you, if you don't know where

270
00:13:50,880 --> 00:13:53,560
Speaker 1: you belong, then you For me, I was a bit

271
00:13:53,640 --> 00:13:56,520
Speaker 1: mischievous too as a result on belonging. I thought, then, okay,

272
00:13:56,559 --> 00:13:57,880
Speaker 1: stuff that I'm not going to do what everyone is

273
00:13:57,920 --> 00:13:59,640
Speaker 1: telling me. To do, but it did drive me to

274
00:13:59,800 --> 00:14:02,040
Speaker 1: try harder. I did. I did try to be really

275
00:14:02,080 --> 00:14:04,960
Speaker 1: competitive because I was determined not let anyone be or anything.

276
00:14:05,000 --> 00:14:07,080
Speaker 2: Oh yeah, I've always been competitive and I did a

277
00:14:07,080 --> 00:14:09,280
Speaker 2: lot of sport. But I also think it comes down

278
00:14:09,320 --> 00:14:13,840
Speaker 2: to my mother was very controlling, so I've always had authority.

279
00:14:14,720 --> 00:14:21,240
Speaker 2: So she let me just think of an example of

280
00:14:21,280 --> 00:14:25,960
Speaker 2: where she was really controlling. So I would have very.

281
00:14:25,880 --> 00:14:30,800
Speaker 1: Strict, very strict like is that does that mean though

282
00:14:30,840 --> 00:14:34,840
Speaker 1: strict about don't wear that short dress? Were correct? Yeah?

283
00:14:34,920 --> 00:14:39,520
Speaker 2: Yeah, so even going to the stroll. So in primary school,

284
00:14:39,520 --> 00:14:43,600
Speaker 2: for example, we didn't have a school uniform, and yet

285
00:14:44,000 --> 00:14:48,760
Speaker 2: Mum made us wear school shoes as though wearing the

286
00:14:48,880 --> 00:14:52,200
Speaker 2: school school uniform. So I would rebel against that. So

287
00:14:52,600 --> 00:14:55,480
Speaker 2: any not only that, you know, I played the piano,

288
00:14:55,680 --> 00:14:58,280
Speaker 2: she would come along to their piano lessons and take notes.

289
00:14:58,760 --> 00:15:01,040
Speaker 2: And then she didn't play the pian herself, and then

290
00:15:01,080 --> 00:15:04,800
Speaker 2: she would instruct me as though she was my piano teacher.

291
00:15:06,040 --> 00:15:08,000
Speaker 2: She wouldn't. She didn't even know how to swim, and

292
00:15:08,000 --> 00:15:10,720
Speaker 2: she come along to the swimming lessons and walk alongside

293
00:15:11,600 --> 00:15:15,320
Speaker 2: the pool, so she was the swimming instructor. And there

294
00:15:15,320 --> 00:15:19,000
Speaker 2: are lots of examples like that, but she was I

295
00:15:19,040 --> 00:15:21,520
Speaker 2: did not get along with my mother very well at all.

296
00:15:21,680 --> 00:15:24,640
Speaker 1: But what do you learn from that as an adult?

297
00:15:24,960 --> 00:15:26,920
Speaker 1: What do you think you learned and what did you

298
00:15:26,920 --> 00:15:29,400
Speaker 1: take out of that social development from what you saw

299
00:15:29,440 --> 00:15:31,360
Speaker 1: with the mother into your adult life and into business.

300
00:15:31,400 --> 00:15:33,720
Speaker 1: For example, So I.

301
00:15:35,480 --> 00:15:39,600
Speaker 2: Neglected to say that my mother was an alcoholic as well.

302
00:15:39,640 --> 00:15:43,080
Speaker 2: That doesn't so I would go to school and face

303
00:15:44,080 --> 00:15:47,040
Speaker 2: bullying and abuse at school, then come home and my

304
00:15:47,120 --> 00:15:51,120
Speaker 2: mother was in her pajamas, depressed, drinking wine. So I

305
00:15:51,160 --> 00:15:53,360
Speaker 2: didn't know what to expect when I got home as well.

306
00:15:54,000 --> 00:15:57,320
Speaker 2: So to answer your question around you know, what did

307
00:15:57,320 --> 00:16:00,440
Speaker 2: that teach me? It would It meant that I would

308
00:16:00,440 --> 00:16:05,480
Speaker 2: surround myself with people who are cheerleaders so very much,

309
00:16:05,520 --> 00:16:07,880
Speaker 2: so I would go my dad was my role model.

310
00:16:08,520 --> 00:16:12,160
Speaker 2: He would leave notes under my pillow, for example, quotes

311
00:16:12,960 --> 00:16:16,000
Speaker 2: that would pick me up. My best friend's mother was

312
00:16:16,240 --> 00:16:19,560
Speaker 2: amazing her family, so I think I took that into

313
00:16:19,600 --> 00:16:23,320
Speaker 2: my career as well. Is to really surround yourself with

314
00:16:23,360 --> 00:16:27,920
Speaker 2: people who who you could trust and who would be

315
00:16:28,080 --> 00:16:29,200
Speaker 2: cheering you on the side.

316
00:16:29,640 --> 00:16:31,640
Speaker 1: In terms of positivity. You're talking about.

317
00:16:31,600 --> 00:16:37,800
Speaker 2: Positivity, but also just yeah, people who would it would

318
00:16:37,800 --> 00:16:41,440
Speaker 2: be your advocates who'd really be there for you. Just

319
00:16:41,520 --> 00:16:42,280
Speaker 2: I've got you back.

320
00:16:42,840 --> 00:16:47,240
Speaker 1: So you've left school? Did you leave school on year twelve?

321
00:16:47,520 --> 00:16:47,720
Speaker 2: Yeap?

322
00:16:47,960 --> 00:16:49,040
Speaker 1: And what did you do off that?

323
00:16:49,880 --> 00:16:54,880
Speaker 2: So? I went to UNI down in Tasmania. I wanted

324
00:16:54,920 --> 00:17:00,120
Speaker 2: to get away from countrytown Victoria and applied everywhere, and

325
00:17:00,160 --> 00:17:05,639
Speaker 2: there just happened to be a big c between mainland exactly,

326
00:17:06,520 --> 00:17:09,560
Speaker 2: that's straight. And I just thought, oh great, this is

327
00:17:09,600 --> 00:17:11,880
Speaker 2: as far as a way possible I can get from

328
00:17:12,040 --> 00:17:13,520
Speaker 2: my parents from.

329
00:17:13,520 --> 00:17:16,080
Speaker 1: You know, ogle from the situation.

330
00:17:16,200 --> 00:17:18,840
Speaker 2: Yeah, exactly, And that's I think that's what I did too.

331
00:17:18,880 --> 00:17:22,879
Speaker 2: I escaped a lot from those situations. And yeah. So

332
00:17:22,920 --> 00:17:26,680
Speaker 2: we went down there and did arts psychology and had

333
00:17:26,680 --> 00:17:30,000
Speaker 2: a great time, absolutely loved it, and then came back

334
00:17:30,040 --> 00:17:32,480
Speaker 2: to the mainland. Didn't know what I wanted to do.

335
00:17:33,680 --> 00:17:37,280
Speaker 2: It was a really tough environment here. So we're talking nineties,

336
00:17:37,320 --> 00:17:39,679
Speaker 2: so it was a recession time, so jobs weren't they

337
00:17:39,720 --> 00:17:40,919
Speaker 2: went that.

338
00:17:41,320 --> 00:17:43,040
Speaker 1: There was a recession the early nineties.

339
00:17:42,800 --> 00:17:46,119
Speaker 2: Yeah, and so I didn't know what to do. And

340
00:17:46,160 --> 00:17:51,000
Speaker 2: I ended up doing a legal administrative course kind of

341
00:17:51,040 --> 00:17:54,359
Speaker 2: like a paralegal course. And I did that and then

342
00:17:54,400 --> 00:17:57,320
Speaker 2: I ended up working at law firm called Filips Fox,

343
00:17:57,320 --> 00:17:59,120
Speaker 2: which in our DLA piper.

344
00:17:59,160 --> 00:18:00,680
Speaker 1: Well pretty big firm.

345
00:18:00,880 --> 00:18:05,639
Speaker 2: Yeah yeah, yeah, So got a job there. I start,

346
00:18:05,680 --> 00:18:08,719
Speaker 2: I started arts admin and then got into a paralegal

347
00:18:08,880 --> 00:18:13,840
Speaker 2: intellectual property paralegal position, and that was yeah, it was

348
00:18:14,240 --> 00:18:17,720
Speaker 2: patents and copyright, trademarks, yeah, trademarks, Pyton.

349
00:18:17,520 --> 00:18:20,720
Speaker 1: Copyright and then we're too from there to Arthur Anderson.

350
00:18:20,960 --> 00:18:27,439
Speaker 2: Arthur the demise of I think they were involved in

351
00:18:27,480 --> 00:18:30,920
Speaker 2: the in Ron right situation.

352
00:18:30,600 --> 00:18:32,479
Speaker 1: Because there was enough the young and and Arthur innoson

353
00:18:32,520 --> 00:18:35,159
Speaker 1: but they both don't exist anymore. Once Gordon it's the

354
00:18:35,200 --> 00:18:38,199
Speaker 1: young but now he was, but I never knew what

355
00:18:38,200 --> 00:18:39,080
Speaker 1: happened Arthur Anderson.

356
00:18:39,400 --> 00:18:44,320
Speaker 2: Yeah, so they essentially with the demise of Enron went.

357
00:18:44,200 --> 00:18:47,840
Speaker 1: Down, right, that were the orders correct, Yeah, famous Enron case,

358
00:18:47,840 --> 00:18:50,280
Speaker 1: one of the greatest collapses in the world of corporate history.

359
00:18:50,400 --> 00:18:53,359
Speaker 2: Exactly. Yeah. So I was working at Arthur Anderson in

360
00:18:53,400 --> 00:18:59,000
Speaker 2: their legal yeah before yeah, before their demise, and then

361
00:18:59,160 --> 00:19:02,760
Speaker 2: when overseas, worked overseas for some law firms over there,

362
00:19:02,880 --> 00:19:06,800
Speaker 2: came back and got into recruitment, into legal recruitment and

363
00:19:07,359 --> 00:19:12,600
Speaker 2: from there, so from there then went out on my

364
00:19:12,680 --> 00:19:18,640
Speaker 2: own and had legal recruitment company, recruiting lawyers for law

365
00:19:18,680 --> 00:19:23,280
Speaker 2: firms and for in house and then yeah, set up

366
00:19:23,320 --> 00:19:25,920
Speaker 2: my own business, had that for ten years, and then

367
00:19:25,920 --> 00:19:30,800
Speaker 2: worked at Deloitte and then post Aloit post Deloitte. Quit

368
00:19:30,840 --> 00:19:37,160
Speaker 2: my job at Deloitte because I always wanted to give

369
00:19:37,200 --> 00:19:40,040
Speaker 2: back to young people like myself. So it's sort of

370
00:19:40,119 --> 00:19:43,920
Speaker 2: come full circle. And I was volunteering at the time

371
00:19:44,040 --> 00:19:47,000
Speaker 2: for an organization called Adopt Change. I don't know if

372
00:19:47,040 --> 00:19:51,080
Speaker 2: you've heard of it before, but founded by Debliefines. What's

373
00:19:51,080 --> 00:19:59,480
Speaker 2: your same Jackman's. Yeah, So she founded this amazing Adopt

374
00:19:59,600 --> 00:20:03,920
Speaker 2: Change organization because she was struggling to adopt children here

375
00:20:03,920 --> 00:20:04,920
Speaker 2: in Australia, so.

376
00:20:04,840 --> 00:20:06,120
Speaker 1: She became really hard.

377
00:20:06,440 --> 00:20:09,000
Speaker 2: It was really tough and it still is tough. So

378
00:20:09,160 --> 00:20:14,239
Speaker 2: the laws, Yes, it's really difficult to adopt now, but

379
00:20:14,280 --> 00:20:16,840
Speaker 2: back then when I was adopted, it was easy. It

380
00:20:16,880 --> 00:20:19,840
Speaker 2: took a year. Now on average it's close to seven

381
00:20:19,920 --> 00:20:20,440
Speaker 2: years or so.

382
00:20:20,640 --> 00:20:22,919
Speaker 1: If you're like you exactly by.

383
00:20:22,760 --> 00:20:25,160
Speaker 2: Which time you've aged out of the process.

384
00:20:25,160 --> 00:20:27,239
Speaker 1: Correct you, So you're too old? Yeah, well they'll think

385
00:20:27,280 --> 00:20:27,720
Speaker 1: you're too old.

386
00:20:27,840 --> 00:20:30,600
Speaker 2: Yeah, a lot more barriers so yeah. So yeah, So

387
00:20:30,680 --> 00:20:33,000
Speaker 2: I was volunteering at the time that I was at Delouche,

388
00:20:33,760 --> 00:20:37,840
Speaker 2: and I realized that I just can't. I can't give

389
00:20:37,920 --> 00:20:41,600
Speaker 2: back in a firm like Deloit, and I really wanted

390
00:20:41,600 --> 00:20:46,920
Speaker 2: to help kids like myself, so those who were really disadvantaged.

391
00:20:47,000 --> 00:20:49,360
Speaker 2: So I thought, I'm going to quit and go out

392
00:20:49,440 --> 00:20:54,360
Speaker 2: and create an organization that inspires young kids, helps young

393
00:20:54,440 --> 00:20:54,840
Speaker 2: kids in.

394
00:20:54,800 --> 00:20:56,879
Speaker 1: Some way, shape or form, and what's that called.

395
00:20:57,359 --> 00:20:59,840
Speaker 2: So I created a company called Spill the Beans, which

396
00:20:59,920 --> 00:21:03,000
Speaker 2: was kind of like hey, Ted talks for kids by kids.

397
00:21:03,240 --> 00:21:05,680
Speaker 1: Okay, it's cool, yeah, which was great.

398
00:21:05,720 --> 00:21:08,200
Speaker 2: So I booked out in the Melbourne Conventions Center, set

399
00:21:08,240 --> 00:21:11,400
Speaker 2: up the company, booked out Melbourne Convention Center for six

400
00:21:11,480 --> 00:21:14,080
Speaker 2: hundred people, started selling tickets, had these great kids ready

401
00:21:14,119 --> 00:21:18,040
Speaker 2: to talk, and then COVID hit oh my god. Yeah,

402
00:21:18,040 --> 00:21:20,159
Speaker 2: I'll never forget that time when the event managed a

403
00:21:20,200 --> 00:21:21,480
Speaker 2: called up and said we.

404
00:21:21,480 --> 00:21:23,600
Speaker 1: Have to specially kids can't bring them.

405
00:21:23,960 --> 00:21:27,600
Speaker 2: Yeah yeah. So so then I thought, what do I

406
00:21:27,640 --> 00:21:29,280
Speaker 2: do now? So I had to pivot very quickly into

407
00:21:29,280 --> 00:21:31,000
Speaker 2: an online offering.

408
00:21:31,920 --> 00:21:34,640
Speaker 1: But for the same thing, same deal, similar So.

409
00:21:35,560 --> 00:21:39,399
Speaker 2: I called it pitch Fest. It was actually young kids

410
00:21:39,400 --> 00:21:44,040
Speaker 2: pitching their business and charity ideas to entrepreneurs. So like

411
00:21:44,240 --> 00:21:47,920
Speaker 2: a mini shark tank, not for investment, for advice. Okay,

412
00:21:48,080 --> 00:21:52,119
Speaker 2: so yeah, they'd pitched their ideas and she was It

413
00:21:52,160 --> 00:21:55,199
Speaker 2: was literally like a mini shark tank for kids. And

414
00:21:55,240 --> 00:22:00,159
Speaker 2: we had amazing yeah yeah exactly. So I had the

415
00:22:00,200 --> 00:22:02,320
Speaker 2: co founder of Netflix on. We had you know, one

416
00:22:02,320 --> 00:22:05,600
Speaker 2: of the sharks from Shark Tank USA, Matt Higgins. We

417
00:22:05,640 --> 00:22:07,920
Speaker 2: had named miss Simpson. We should have had you on, Mark.

418
00:22:09,359 --> 00:22:12,119
Speaker 2: We had all these amazing entrepreneurs on the show and

419
00:22:12,280 --> 00:22:16,440
Speaker 2: created this this production. But it was costing me a

420
00:22:16,480 --> 00:22:18,080
Speaker 2: lot of money to produce.

421
00:22:18,440 --> 00:22:20,120
Speaker 1: Yeah, so in which weren't making money.

422
00:22:20,160 --> 00:22:22,640
Speaker 2: I wasn't making money exactly. So then I thought, how

423
00:22:22,640 --> 00:22:26,440
Speaker 2: do I turn this into something that can make money from.

424
00:22:26,359 --> 00:22:27,560
Speaker 1: A proper business model?

425
00:22:27,720 --> 00:22:31,240
Speaker 2: Yeah yeah, So I turned it into an educational resource

426
00:22:31,800 --> 00:22:34,160
Speaker 2: and then started teaching it in school. So schools were

427
00:22:34,160 --> 00:22:39,600
Speaker 2: paying me to facilitate these ideation workshops with schools, teaching

428
00:22:39,720 --> 00:22:41,480
Speaker 2: kids how to bring their ideas.

429
00:22:41,119 --> 00:22:43,680
Speaker 1: To life at a school at schoolchools.

430
00:22:44,000 --> 00:22:44,400
Speaker 2: Yeah.

431
00:22:44,480 --> 00:22:46,840
Speaker 1: So did you have to do a deal with your

432
00:22:46,920 --> 00:22:49,880
Speaker 1: Victorian but you have to deal with the Victorian government, No,

433
00:22:50,000 --> 00:22:50,199
Speaker 1: I know.

434
00:22:50,480 --> 00:22:53,240
Speaker 2: So the schools that I approached just said we'll pay

435
00:22:53,280 --> 00:22:55,639
Speaker 2: you to come in and do these ideation workshops with

436
00:22:55,680 --> 00:22:58,240
Speaker 2: the kids and help them bring their ideas to life.

437
00:22:58,680 --> 00:23:01,840
Speaker 1: So like the work that you do in the schools

438
00:23:01,920 --> 00:23:06,840
Speaker 1: is helping kids think about an idea for business and

439
00:23:06,880 --> 00:23:08,920
Speaker 1: then or is it about they've already got an idea

440
00:23:08,960 --> 00:23:10,600
Speaker 1: for business, and how do I bring this life by

441
00:23:10,760 --> 00:23:14,360
Speaker 1: teaching them how to perhaps pitch the best right both.

442
00:23:14,240 --> 00:23:19,600
Speaker 2: So bringing thinking of ideas based on problems that they

443
00:23:19,600 --> 00:23:23,040
Speaker 2: were trying to solve, and then going through the ideation

444
00:23:23,359 --> 00:23:26,720
Speaker 2: process of right where to Now, how do we validate

445
00:23:26,760 --> 00:23:29,680
Speaker 2: these ideas and then how do we execute on those

446
00:23:29,720 --> 00:23:32,960
Speaker 2: ideas and sort of entrepreneurship in the name of the business.

447
00:23:33,040 --> 00:23:36,840
Speaker 2: So it's still spill the beans now and now, So

448
00:23:36,920 --> 00:23:38,439
Speaker 2: that's kind of morphed into solve it.

449
00:23:39,240 --> 00:23:40,480
Speaker 1: So which is your new business?

450
00:23:40,880 --> 00:23:41,639
Speaker 2: Yes? Correct?

451
00:23:41,720 --> 00:23:46,080
Speaker 1: And that's now just quickly summarize solve it for me

452
00:23:46,080 --> 00:23:47,360
Speaker 1: because and then I want to go to the bring

453
00:23:47,320 --> 00:23:48,800
Speaker 1: and when I come back, I want to talk about

454
00:23:48,840 --> 00:23:51,120
Speaker 1: solve it. Yeah, I can't say it, probably because I've

455
00:23:51,160 --> 00:23:53,080
Speaker 1: seen the spelling of it as x l o V

456
00:23:53,240 --> 00:23:56,119
Speaker 1: I t o l V was close.

457
00:23:56,480 --> 00:23:58,679
Speaker 2: Yeah, So like think of xerox zero.

458
00:24:00,400 --> 00:24:04,159
Speaker 1: So what is resolved? Just take me through to the

459
00:24:04,200 --> 00:24:06,840
Speaker 1: final conclusion, where soolved is now obviously is going to

460
00:24:06,840 --> 00:24:09,760
Speaker 1: have more iterations as you go on, But where Resolveds

461
00:24:09,760 --> 00:24:13,400
Speaker 1: sit right now in terms of you're offering it's out.

462
00:24:13,200 --> 00:24:17,520
Speaker 2: In the market now. Yeah, so we're teaching at universities.

463
00:24:16,600 --> 00:24:18,360
Speaker 1: So you've gone beyond schools.

464
00:24:17,920 --> 00:24:21,640
Speaker 2: Beyond schools universities. It's of course companies are paying for it.

465
00:24:22,160 --> 00:24:23,600
Speaker 2: I'll talk to you in more detail about it, but

466
00:24:23,680 --> 00:24:27,920
Speaker 2: essentially what it is is a crowdsourcing app for student

467
00:24:28,000 --> 00:24:32,280
Speaker 2: innovation helping companies to solve social problems.

468
00:24:32,040 --> 00:24:34,840
Speaker 1: Stayed again, So it's a crowd stay it against.

469
00:24:34,840 --> 00:24:38,520
Speaker 2: So it's an app companies with students.

470
00:24:38,560 --> 00:24:40,720
Speaker 1: So it's a marketplace in that regard. So you've got

471
00:24:40,720 --> 00:24:43,760
Speaker 1: students over here and you've got corporations over here, correct,

472
00:24:43,960 --> 00:24:47,200
Speaker 1: and what are the students putting onto the marketplace?

473
00:24:47,680 --> 00:24:51,200
Speaker 2: So companies create challenges on the app that are aligned

474
00:24:51,240 --> 00:24:55,080
Speaker 2: to the United Nations Sustainable Development goals in relation to

475
00:24:55,240 --> 00:24:59,320
Speaker 2: real problems that they're facing, and then students pitch their ideas,

476
00:25:00,160 --> 00:25:03,640
Speaker 2: then win the opportunity to meet the executives of those

477
00:25:03,640 --> 00:25:06,160
Speaker 2: companies and potentially built up their ideas with the companies.

478
00:25:06,200 --> 00:25:08,320
Speaker 1: So they picture there idea about how to solve the problem.

479
00:25:08,400 --> 00:25:12,679
Speaker 1: So BHP put a question up there about whatever, is

480
00:25:12,680 --> 00:25:16,080
Speaker 1: there a mandate as to what as to what areas?

481
00:25:16,440 --> 00:25:18,920
Speaker 1: Is it mandated as to what areas can be put

482
00:25:18,960 --> 00:25:20,000
Speaker 1: on there for.

483
00:25:19,840 --> 00:25:22,600
Speaker 2: Solving Yes, so they have to be aligned to the

484
00:25:22,680 --> 00:25:26,119
Speaker 2: United Nations. What is that though, sdbs SG So you

485
00:25:26,160 --> 00:25:29,320
Speaker 2: know the SDGs, No, I don't, Okay, So the STGs,

486
00:25:29,400 --> 00:25:31,960
Speaker 2: the United Nations have put out basically a blueprint for

487
00:25:32,000 --> 00:25:36,000
Speaker 2: the future around They've set seventeen goals that they want

488
00:25:36,040 --> 00:25:39,960
Speaker 2: to achieve by twenty thirty and it might be poverty,

489
00:25:40,080 --> 00:25:44,119
Speaker 2: no poverty, zero hunger, gender equality like we have you know,

490
00:25:44,240 --> 00:25:46,679
Speaker 2: equal amount of men and women in the workforce, or

491
00:25:47,080 --> 00:25:50,480
Speaker 2: just there are seventeen of these goals, climate action for example.

492
00:25:50,960 --> 00:25:53,200
Speaker 2: So I'll give an example of one of the challenges

493
00:25:53,320 --> 00:25:56,320
Speaker 2: is on the platform. So Village Cinemas is on the platform.

494
00:25:56,359 --> 00:25:59,280
Speaker 2: For example, They've created a challenge that relates to getting

495
00:25:59,280 --> 00:26:02,160
Speaker 2: more people through the cinemas, helping to create more mental

496
00:26:02,200 --> 00:26:05,280
Speaker 2: health and wellbeing for people. Because during COVID it was

497
00:26:05,320 --> 00:26:09,880
Speaker 2: all lockdown and everyone was using streaming platforms. So they've

498
00:26:09,880 --> 00:26:13,160
Speaker 2: put a challenge on their in relation to SDG nine,

499
00:26:13,240 --> 00:26:17,400
Speaker 2: which is industry and innovation, how do we attract more

500
00:26:17,560 --> 00:26:21,840
Speaker 2: people through the cinemas? So go on and solve it.

501
00:26:22,080 --> 00:26:25,439
Speaker 1: And kids and the challenge. Now, well, I'm going to

502
00:26:25,440 --> 00:26:27,520
Speaker 1: get come straight back. But when I come back, I

503
00:26:27,560 --> 00:26:28,919
Speaker 1: want to talk to you, talk to you about sort of a

504
00:26:28,920 --> 00:26:31,240
Speaker 1: bit more, get into the weeds of how it all works,

505
00:26:31,560 --> 00:26:40,119
Speaker 1: if you don't mind. I'm back from the break and

506
00:26:40,160 --> 00:26:44,280
Speaker 1: I'm here with Vegan and we are talking about resolve it.

507
00:26:44,520 --> 00:26:47,600
Speaker 1: I can't even bloody pronounce it, but as I've got

508
00:26:47,640 --> 00:26:49,159
Speaker 1: to hear in front of me, x O, l V

509
00:26:49,320 --> 00:26:51,360
Speaker 1: I T, and I presume it's resolve it dot com

510
00:26:51,400 --> 00:26:55,360
Speaker 1: dot or just solve it dot io, dot I io

511
00:26:55,520 --> 00:26:55,800
Speaker 1: what I.

512
00:26:56,040 --> 00:26:59,480
Speaker 2: Stand for now, it's just a fancy tech.

513
00:27:01,040 --> 00:27:02,560
Speaker 1: It's just but as new tech domain, is it?

514
00:27:02,680 --> 00:27:02,840
Speaker 2: Yes?

515
00:27:03,000 --> 00:27:07,600
Speaker 1: Okay? X O, l V I T, dot io. And

516
00:27:08,240 --> 00:27:12,280
Speaker 1: you know, in my simple terms, it's a marketplace between

517
00:27:12,640 --> 00:27:16,280
Speaker 1: let's call it corporations who are trying to have been

518
00:27:16,920 --> 00:27:23,240
Speaker 1: adopting the mandates of the Sustainable Development Goals goals thank you,

519
00:27:24,840 --> 00:27:26,879
Speaker 1: which is sort of like the mandate coming out of

520
00:27:26,880 --> 00:27:28,680
Speaker 1: the United Nations. And I think there's did you say

521
00:27:28,680 --> 00:27:31,000
Speaker 1: seventeen of the seventeen of these seven en goals, so

522
00:27:31,000 --> 00:27:33,160
Speaker 1: they can pick any goal they want, whatever it is,

523
00:27:33,560 --> 00:27:36,760
Speaker 1: so they can pick numerous goals. They put the challenge up,

524
00:27:36,880 --> 00:27:39,239
Speaker 1: or they put the problem up, or the challenge up

525
00:27:39,280 --> 00:27:43,760
Speaker 1: onto the onto your website. Then kids, I'll presume anywhere.

526
00:27:43,440 --> 00:27:46,200
Speaker 2: In the world university students, but anywhere in the world.

527
00:27:46,880 --> 00:27:50,400
Speaker 1: Just aus trailer, just Astralia the moment, but Australian university students.

528
00:27:50,440 --> 00:27:52,520
Speaker 1: And it doesn't really matter with it in year one

529
00:27:52,560 --> 00:27:55,639
Speaker 1: or year it doesn't matter if it's it doesn't matter

530
00:27:55,720 --> 00:28:00,640
Speaker 1: the courses. Does anyone any goods? And they then put

531
00:28:00,720 --> 00:28:04,520
Speaker 1: up suggestion how that this particular thing can be met,

532
00:28:04,600 --> 00:28:06,440
Speaker 1: this goal can be met, and this challenge can be solved.

533
00:28:06,960 --> 00:28:11,840
Speaker 1: But what actually happens when let's say, you know, my

534
00:28:11,920 --> 00:28:14,439
Speaker 1: grandson puts it up. Yep, he's not at university at

535
00:28:14,440 --> 00:28:16,640
Speaker 1: the moment, he's too young, but thetume is a university.

536
00:28:16,960 --> 00:28:18,879
Speaker 1: He puts up one of these solutions. What actually happens,

537
00:28:18,920 --> 00:28:22,040
Speaker 1: does let's call it village road shows put up the

538
00:28:22,119 --> 00:28:25,960
Speaker 1: issue as you suggested, Does the CEO get him, does

539
00:28:25,960 --> 00:28:26,960
Speaker 1: he get a mentor.

540
00:28:26,840 --> 00:28:29,000
Speaker 2: What does he get so he gets to our ideation

541
00:28:29,119 --> 00:28:32,600
Speaker 2: workshop with the company with the executives from the company,

542
00:28:32,600 --> 00:28:35,720
Speaker 2: so whoever they choose to bring into that ideation workshop.

543
00:28:35,760 --> 00:28:38,360
Speaker 2: So we did one recently with Microsoft, so Microsoft is

544
00:28:38,360 --> 00:28:43,360
Speaker 2: on the platform. They created an AI challenge. An NBA

545
00:28:43,440 --> 00:28:46,800
Speaker 2: student from Melbourne Business School pitch their challenge won that opportunity.

546
00:28:47,120 --> 00:28:52,240
Speaker 2: We had a group of executives from Microsoft and Melbourne

547
00:28:52,240 --> 00:28:55,400
Speaker 2: Business School attended to our ideation workshop to help build

548
00:28:55,400 --> 00:28:57,800
Speaker 2: out this idea. You know, what would it look like,

549
00:28:57,840 --> 00:29:01,720
Speaker 2: so to ideate around potentially bringing that to life.

550
00:29:01,800 --> 00:29:04,760
Speaker 1: So an NBA student unfair because he's probably already got

551
00:29:04,800 --> 00:29:08,240
Speaker 1: a degree or she's got a degree, but it doesn't matter.

552
00:29:09,040 --> 00:29:11,640
Speaker 1: So the NBA it's great anyway. So the NBA students,

553
00:29:11,640 --> 00:29:14,640
Speaker 1: now incentivized to do something, gets an opportunity to meet

554
00:29:14,760 --> 00:29:19,640
Speaker 1: up with these with Microsoft execs. Does Microsoft then say,

555
00:29:19,800 --> 00:29:25,280
Speaker 1: in terms of building this AI model out which involves software,

556
00:29:26,240 --> 00:29:28,840
Speaker 1: does Microsoft lend them any resources?

557
00:29:29,920 --> 00:29:33,240
Speaker 2: So it's really just an idea at the moment. It's

558
00:29:33,320 --> 00:29:36,440
Speaker 2: just this is what it could look like. This, maybe

559
00:29:36,480 --> 00:29:39,120
Speaker 2: we build it out, maybe we take certain parts of

560
00:29:39,120 --> 00:29:41,920
Speaker 2: this and work on this in the future. But it's

561
00:29:42,040 --> 00:29:44,640
Speaker 2: not you know, we're not taking your IP for example, okay,

562
00:29:45,360 --> 00:29:49,160
Speaker 2: stealing your IP to go and build out your product specifically,

563
00:29:49,800 --> 00:29:53,080
Speaker 2: So it's really just an opportunity to more. It's more

564
00:29:53,080 --> 00:29:56,560
Speaker 2: about the connection from the student and the company connecting,

565
00:29:56,640 --> 00:29:59,120
Speaker 2: coming together, and that's what the students want. So we're

566
00:29:59,160 --> 00:30:02,440
Speaker 2: solving that problem for the students and then for the companies,

567
00:30:02,480 --> 00:30:05,760
Speaker 2: we're helping them to raise brand awareness with amazing students

568
00:30:05,760 --> 00:30:07,120
Speaker 2: across universities.

569
00:30:07,200 --> 00:30:11,000
Speaker 1: To companies do this out of their corporations, do this

570
00:30:11,040 --> 00:30:14,720
Speaker 1: out of their obligation to do community stuff like things

571
00:30:14,720 --> 00:30:16,320
Speaker 1: for communities. Is it part of it?

572
00:30:16,320 --> 00:30:19,800
Speaker 2: It's doing good in the world for them, And maybe

573
00:30:19,800 --> 00:30:22,000
Speaker 2: you want to talk about this after the break, but

574
00:30:22,440 --> 00:30:25,440
Speaker 2: there are lots of reasons why companies want to do this.

575
00:30:27,080 --> 00:30:30,560
Speaker 2: The first is that they're trying to deal with the

576
00:30:30,600 --> 00:30:35,480
Speaker 2: problem that they're losing graduates. So the graduate reneg rates

577
00:30:35,840 --> 00:30:38,160
Speaker 2: are at the highest they've ever been right now. So

578
00:30:38,240 --> 00:30:42,560
Speaker 2: graduates are applying for positions at many companies, they're getting

579
00:30:42,560 --> 00:30:46,160
Speaker 2: offered positions, but then they're renegging on their offers.

580
00:30:46,240 --> 00:30:47,600
Speaker 1: But doing what that after.

581
00:30:47,400 --> 00:30:53,280
Speaker 2: The reneq going to one company, So twenty applications out there,

582
00:30:53,800 --> 00:30:55,960
Speaker 2: they'll choose one offer to go with one company. Yeah,

583
00:30:56,720 --> 00:30:58,680
Speaker 2: so they're renegging on their office and it's the highest

584
00:30:58,720 --> 00:31:00,840
Speaker 2: that it's ever been. It's the twenty five percent, and

585
00:31:00,880 --> 00:31:03,520
Speaker 2: that's costing companies at the moment like two point six

586
00:31:03,600 --> 00:31:07,840
Speaker 2: million per year for example the other So that's that's

587
00:31:07,840 --> 00:31:10,440
Speaker 2: solving a problem for them because they're trying to attract

588
00:31:10,920 --> 00:31:13,760
Speaker 2: but they're not attracting them because they're going elsewhere. And

589
00:31:13,800 --> 00:31:16,640
Speaker 2: the reason that they're not attracting them is because they're

590
00:31:16,640 --> 00:31:22,120
Speaker 2: not necessarily aligned with the student's social values. So in

591
00:31:22,160 --> 00:31:24,480
Speaker 2: our sort of customer discovery that we did for Zolvers,

592
00:31:25,240 --> 00:31:29,000
Speaker 2: we found that a lot of students will leave or

593
00:31:29,040 --> 00:31:31,840
Speaker 2: graduates will leave a position, and gen Z in particular,

594
00:31:31,920 --> 00:31:34,680
Speaker 2: will leave a position within a couple of years if

595
00:31:34,680 --> 00:31:36,920
Speaker 2: they're not socially aligned with the company. So if they

596
00:31:36,960 --> 00:31:39,640
Speaker 2: don't feel that your company is making a societal impact,

597
00:31:40,760 --> 00:31:44,080
Speaker 2: see you later, and they will lose their workforce.

598
00:31:44,240 --> 00:31:46,080
Speaker 1: What do you mean? But what do they mean by

599
00:31:46,200 --> 00:31:48,239
Speaker 1: when you did you research? What does it mean that

600
00:31:49,040 --> 00:31:52,880
Speaker 1: for a company to be socially aligned with that Z person?

601
00:31:52,920 --> 00:31:54,080
Speaker 1: For example, what.

602
00:31:56,320 --> 00:31:59,040
Speaker 2: If they feel like you're not contributing to the community,

603
00:31:59,120 --> 00:32:02,400
Speaker 2: for example, doing volunteer work in some way, or you

604
00:32:02,440 --> 00:32:06,200
Speaker 2: don't have a you're not donating money to foundations, or

605
00:32:06,240 --> 00:32:09,360
Speaker 2: if you don't have a carbon footprint, some kind of

606
00:32:09,400 --> 00:32:14,040
Speaker 2: EESG strategy across a number of social issues. If you

607
00:32:14,040 --> 00:32:17,800
Speaker 2: don't have that in place in your policies, then gensit

608
00:32:17,840 --> 00:32:20,719
Speaker 2: are not interested in you. Because they really care about

609
00:32:20,800 --> 00:32:23,800
Speaker 2: the world. They really care about gender equality, they care

610
00:32:23,840 --> 00:32:28,120
Speaker 2: about diversity inclusion, they care about the climate. There's so

611
00:32:28,240 --> 00:32:31,640
Speaker 2: many things. And if your company is not aligned socially

612
00:32:31,720 --> 00:32:35,560
Speaker 2: with these values, then they're going to choose another company

613
00:32:35,600 --> 00:32:38,400
Speaker 2: over here that is more attractive for them. So that's

614
00:32:38,600 --> 00:32:40,840
Speaker 2: a problem that they're currently facing.

615
00:32:41,320 --> 00:32:46,160
Speaker 1: So when you pick the United Nations seventeen let's call

616
00:32:46,200 --> 00:32:51,600
Speaker 1: it chapters, that they have obviously carefully considered the seventeen

617
00:32:52,440 --> 00:32:55,000
Speaker 1: social issues that are probably existing in the world today.

618
00:32:56,120 --> 00:32:59,000
Speaker 1: I guess they're not expecting it to be exhausted, but

619
00:32:59,120 --> 00:33:03,560
Speaker 1: be fairly exhausted. It's probably easier then for corporations just

620
00:33:03,560 --> 00:33:05,160
Speaker 1: to adopt one of those because they at least an

621
00:33:05,240 --> 00:33:08,840
Speaker 1: they're in a safe space. They're picking something that is relevant. Yes,

622
00:33:08,880 --> 00:33:13,280
Speaker 1: and so your your app actually is it a web

623
00:33:13,280 --> 00:33:16,240
Speaker 1: app or an actual app, it's an app you but

624
00:33:16,320 --> 00:33:19,400
Speaker 1: your program anyway allow gives them this opportunity to become

625
00:33:20,480 --> 00:33:21,680
Speaker 1: or to stay relevant.

626
00:33:21,920 --> 00:33:25,160
Speaker 2: Yes, to young people the future workforce.

627
00:33:25,880 --> 00:33:29,400
Speaker 1: And Okay, that's interesting, and so it is sort of

628
00:33:29,440 --> 00:33:34,160
Speaker 1: a bit of a branding exercise, but there's also relevancy exercise.

629
00:33:34,200 --> 00:33:38,360
Speaker 1: Got I guess branding is about relevancy, relevancy and branding

630
00:33:38,480 --> 00:33:41,680
Speaker 1: in relation to recruitment, because if you can't recruit, you

631
00:33:41,760 --> 00:33:42,200
Speaker 1: in trouble.

632
00:33:42,400 --> 00:33:47,200
Speaker 2: Correct. So, really, what's overd is is a clever pre

633
00:33:47,320 --> 00:33:50,920
Speaker 2: screening recruits tool for companies and.

634
00:33:50,920 --> 00:33:53,400
Speaker 1: For students, and for both for students as well, because

635
00:33:53,440 --> 00:33:55,480
Speaker 1: the student gets to look at these guys aren't genuine

636
00:33:55,560 --> 00:33:59,360
Speaker 1: or they are genuine or they you know, they they

637
00:33:59,360 --> 00:34:01,280
Speaker 1: believe what I'm what I believe, and so it's not

638
00:34:01,360 --> 00:34:03,959
Speaker 1: really it's sort of like a it's sort of like

639
00:34:04,520 --> 00:34:08,560
Speaker 1: a dating apport between corporations.

640
00:34:08,600 --> 00:34:11,719
Speaker 2: Say that socially responsible dating, Yeah, totally.

641
00:34:11,760 --> 00:34:14,120
Speaker 1: Yeah. Yeah, it's not people just turning up to their

642
00:34:14,120 --> 00:34:16,040
Speaker 1: house or something that. But it's like actual you know,

643
00:34:16,120 --> 00:34:19,280
Speaker 1: like hanging out together and sort of getting an opportunity

644
00:34:19,280 --> 00:34:20,600
Speaker 1: to meet each other and talk to each other.

645
00:34:20,680 --> 00:34:21,439
Speaker 2: Yeah, that's right.

646
00:34:21,640 --> 00:34:25,040
Speaker 1: And so what's the business model on it though, Helen?

647
00:34:25,280 --> 00:34:28,760
Speaker 2: So for you, yes, yeah, so companies pay.

648
00:34:28,560 --> 00:34:31,720
Speaker 1: They pay to be to be on the site. Correct.

649
00:34:31,719 --> 00:34:34,600
Speaker 2: So companies. The value for the companies is that it's

650
00:34:34,680 --> 00:34:40,080
Speaker 2: raising brand awareness to university students, and it's it's gaining talent,

651
00:34:40,800 --> 00:34:43,720
Speaker 2: and it's also youthful perspectives and innovation.

652
00:34:44,000 --> 00:34:45,920
Speaker 1: That's sort of part of their recruitment program. So they

653
00:34:45,960 --> 00:34:47,480
Speaker 1: might end up in seek or something like that. But

654
00:34:47,800 --> 00:34:50,239
Speaker 1: really what they're doing here is as sussing out there.

655
00:34:50,400 --> 00:34:52,719
Speaker 1: They're allowing others to suss them out, and they're going

656
00:34:52,719 --> 00:34:54,799
Speaker 1: to the nursery, which is university is one of the

657
00:34:55,239 --> 00:34:58,680
Speaker 1: one of the nurseries and universities to find out who

658
00:34:58,760 --> 00:35:01,680
Speaker 1: wants to actually tackle the issue. Do people get an

659
00:35:01,680 --> 00:35:03,400
Speaker 1: award or something like let's say I'm a student, I

660
00:35:03,520 --> 00:35:04,920
Speaker 1: go on there and I design you for you know

661
00:35:04,920 --> 00:35:07,600
Speaker 1: whoever it is Microsoft? Do they get a certificate as.

662
00:35:07,680 --> 00:35:10,240
Speaker 2: Yes they do. Yeah, they get a certificate of achievement

663
00:35:10,280 --> 00:35:13,440
Speaker 2: to say I've solved. I'm assolver for Microsoft or I'm

664
00:35:13,440 --> 00:35:14,280
Speaker 2: resolver for Iba.

665
00:35:14,360 --> 00:35:19,040
Speaker 1: What do you call it? As over okay? And as

666
00:35:19,080 --> 00:35:21,560
Speaker 1: it competitive? So in other words that let's say Microsoft

667
00:35:21,600 --> 00:35:24,640
Speaker 1: puts this thing out there, Yeah, to twenty people, do

668
00:35:24,719 --> 00:35:25,239
Speaker 1: they pick one?

669
00:35:25,719 --> 00:35:28,440
Speaker 2: They pick one out of twenty or fifty exactly?

670
00:35:28,520 --> 00:35:30,720
Speaker 1: Do you any much flow through here? Like in terms

671
00:35:30,719 --> 00:35:31,799
Speaker 1: of students.

672
00:35:32,160 --> 00:35:35,160
Speaker 2: Yeah, so we're just we literally only just launched this year.

673
00:35:35,480 --> 00:35:39,440
Speaker 2: But yeah, So how we're changing the education system in

674
00:35:39,480 --> 00:35:42,200
Speaker 2: a way is that this has been if you think

675
00:35:42,200 --> 00:35:46,160
Speaker 2: of it as a you know, the flywheel, it's a

676
00:35:46,239 --> 00:35:48,799
Speaker 2: double sided marketplace, right, So you've got the students who

677
00:35:48,840 --> 00:35:51,040
Speaker 2: are the users, and you've got companies that create the

678
00:35:51,120 --> 00:35:56,120
Speaker 2: demand and the universities provide the supply of the students.

679
00:35:56,600 --> 00:35:59,239
Speaker 2: So in terms of getting students on the way that

680
00:35:59,280 --> 00:36:02,440
Speaker 2: we acquire students onto the platform is actually by teaching

681
00:36:02,440 --> 00:36:05,719
Speaker 2: it in class. So you'll probably remember from your days

682
00:36:05,719 --> 00:36:08,440
Speaker 2: at UNI, you probably studied a lot of Harvard business

683
00:36:08,440 --> 00:36:09,200
Speaker 2: case studies.

684
00:36:09,880 --> 00:36:12,880
Speaker 1: I actually I have taught them in them in my

685
00:36:14,000 --> 00:36:15,120
Speaker 1: teaching career at the university.

686
00:36:15,320 --> 00:36:18,480
Speaker 2: Yeah yeah, so I guess Soolve it in a way

687
00:36:18,760 --> 00:36:24,520
Speaker 2: is substituting the h Harvard Business case studies. So instead

688
00:36:24,560 --> 00:36:27,200
Speaker 2: of jumping, you know, a lecturer standing up in front

689
00:36:27,200 --> 00:36:30,200
Speaker 2: of class saying, hey, we're going to study a Harvard

690
00:36:30,200 --> 00:36:32,520
Speaker 2: business case study, we're going to jump on the Zolve platform.

691
00:36:32,920 --> 00:36:36,520
Speaker 2: So they'll actually use it as a formal assessment teaching

692
00:36:36,560 --> 00:36:40,240
Speaker 2: a correct Yeah. Yeah, so they'll do a formal assessment

693
00:36:40,280 --> 00:36:43,280
Speaker 2: in relation to deep diving into the actual problem itself,

694
00:36:43,719 --> 00:36:47,359
Speaker 2: coming up with a business recommendation report, and then they'll

695
00:36:47,400 --> 00:36:49,880
Speaker 2: do a pitching assessment as well.

696
00:36:50,560 --> 00:36:51,920
Speaker 1: Use apply all the training for that.

697
00:36:52,280 --> 00:36:56,120
Speaker 2: Yeah. Yeah, So we provide an education guide and formal

698
00:36:56,160 --> 00:36:59,960
Speaker 2: assessment briefs and rebricks to the lecturers to teach it in.

699
00:37:00,120 --> 00:37:03,600
Speaker 1: So is the source of the students getting onto the

700
00:37:03,600 --> 00:37:06,840
Speaker 1: problem that needs to be solved in this is in class,

701
00:37:07,400 --> 00:37:11,000
Speaker 1: through the through the university. So is your game to

702
00:37:11,000 --> 00:37:14,520
Speaker 1: sign universities up? Correct? So that's what you do, pert

703
00:37:14,960 --> 00:37:16,960
Speaker 1: you and your team, So you go to the university,

704
00:37:17,000 --> 00:37:19,359
Speaker 1: you pitch your idea why they should do it, what's

705
00:37:19,400 --> 00:37:21,000
Speaker 1: in it for the universities.

706
00:37:20,640 --> 00:37:23,279
Speaker 2: So a number of things for them. It's their work

707
00:37:23,320 --> 00:37:27,720
Speaker 2: integrated learning experience for the students. So students do obviously

708
00:37:27,719 --> 00:37:31,160
Speaker 2: who come through the program get to win this potential

709
00:37:31,160 --> 00:37:33,840
Speaker 2: opportunity with the company. So it's a connection of industry

710
00:37:34,400 --> 00:37:37,520
Speaker 2: with the students. But also a lot of you know,

711
00:37:37,560 --> 00:37:40,200
Speaker 2: students are dropping out of classes at the moment too

712
00:37:40,400 --> 00:37:44,320
Speaker 2: because they're not feeling engaged. It's currently twenty.

713
00:37:44,080 --> 00:37:46,319
Speaker 1: Six percent because the courses of relevant I'm not so

714
00:37:46,400 --> 00:37:48,800
Speaker 1: grazed respect to the university I'm at you in a study,

715
00:37:49,560 --> 00:37:51,720
Speaker 1: you know, school business. I find the course of relevant.

716
00:37:51,760 --> 00:37:53,960
Speaker 1: I mean most of the subjects are irrelevant. The students

717
00:37:54,000 --> 00:37:56,080
Speaker 1: have worked it out. Yeah, say what am I doing

718
00:37:56,120 --> 00:37:58,120
Speaker 1: in a three year degree for cost me fifty grand?

719
00:37:58,560 --> 00:38:00,000
Speaker 1: And I'm doing I could have done it one year

720
00:38:00,000 --> 00:38:01,520
Speaker 1: because there any stuff I really want to know about

721
00:38:01,600 --> 00:38:02,360
Speaker 1: is blah blah and.

722
00:38:03,520 --> 00:38:06,080
Speaker 2: Yeah, and they're preferring to go and work and get money,

723
00:38:06,680 --> 00:38:11,480
Speaker 2: whether it's a subway, KFC wherever it is, attend to yeah, exactly,

724
00:38:11,680 --> 00:38:16,120
Speaker 2: or entrepreneurship then attend class. So universities are losing students

725
00:38:16,120 --> 00:38:18,920
Speaker 2: in that way. They need to engage them. So for universities,

726
00:38:19,160 --> 00:38:23,000
Speaker 2: it's about engaging them in an interesting, fun, practical way

727
00:38:23,080 --> 00:38:25,720
Speaker 2: because they all hate theoretical like you know, the Harvard

728
00:38:25,719 --> 00:38:28,480
Speaker 2: business case studies. We're sick and tired of these studies.

729
00:38:29,239 --> 00:38:33,000
Speaker 2: Let's bring practice into the class. So it's solving a

730
00:38:33,000 --> 00:38:35,920
Speaker 2: problem for universities in that way. But also you've probably

731
00:38:35,920 --> 00:38:39,200
Speaker 2: come across lecturers. They have a very limited resource in

732
00:38:39,280 --> 00:38:41,560
Speaker 2: terms of the industry people that they know because they

733
00:38:41,600 --> 00:38:44,080
Speaker 2: haven't worked in industry, and they keep calling on their

734
00:38:44,160 --> 00:38:47,400
Speaker 2: mates to come into class. But there's so much you

735
00:38:47,440 --> 00:38:50,319
Speaker 2: can do so solve. It helps bring a number of

736
00:38:50,360 --> 00:38:52,240
Speaker 2: companies into the classroom.

737
00:38:52,640 --> 00:38:55,320
Speaker 1: And so would Microsoft, for example, come into the classroom.

738
00:38:55,640 --> 00:38:57,640
Speaker 2: They can. Now it's up to the lecturer. We can

739
00:38:57,760 --> 00:38:59,400
Speaker 2: organize that for them. I guess we're sort of that

740
00:38:59,480 --> 00:39:04,160
Speaker 2: conduit between the industry partners and the universities. But it's

741
00:39:04,280 --> 00:39:07,960
Speaker 2: it's really so when the companies actually promote their challenges

742
00:39:08,000 --> 00:39:11,880
Speaker 2: on a platform, you've got the executives recording themselves promoting

743
00:39:11,880 --> 00:39:14,200
Speaker 2: the challenge on the platform too, So it's quite engaging.

744
00:39:14,480 --> 00:39:16,799
Speaker 1: Do you have to train the executives because it means

745
00:39:16,520 --> 00:39:21,440
Speaker 1: my experience with some of these executives is that with

746
00:39:21,600 --> 00:39:23,640
Speaker 1: a gress respect, they're not very good in front of

747
00:39:23,680 --> 00:39:25,880
Speaker 1: a camera and a lot of them other all that

748
00:39:26,000 --> 00:39:30,040
Speaker 1: exciting or don't really motivate. They're not really motivated.

749
00:39:29,719 --> 00:39:31,200
Speaker 2: To provide the script for them.

750
00:39:31,480 --> 00:39:35,480
Speaker 1: So it's really actually write it out, do yeah, okay, yes,

751
00:39:35,640 --> 00:39:39,680
Speaker 1: change abuty or open. So are you actually using AI

752
00:39:39,760 --> 00:39:43,080
Speaker 1: for this stuff? We are, So they give you instructions.

753
00:39:42,920 --> 00:39:45,799
Speaker 2: So or we make it really low barrier for the

754
00:39:45,840 --> 00:39:48,480
Speaker 2: companies to come on. We say, give us a topic

755
00:39:48,520 --> 00:39:50,680
Speaker 2: in relation to a problem that you're solving. So a

756
00:39:50,680 --> 00:39:53,200
Speaker 2: brief as in a just just give us one topic

757
00:39:53,440 --> 00:39:55,560
Speaker 2: in relation to something you're struggling with. It might be

758
00:39:55,600 --> 00:39:59,399
Speaker 2: a paragraph, it could be a word. It could be say,

759
00:39:59,440 --> 00:40:02,359
Speaker 2: for example, Ronald McDonald house, I want to come onto

760
00:40:02,360 --> 00:40:05,480
Speaker 2: the platform. We're struggling with food waste in relation to

761
00:40:06,640 --> 00:40:09,400
Speaker 2: you know that our houses come up with a challenge

762
00:40:09,400 --> 00:40:10,080
Speaker 2: that relates to that.

763
00:40:10,239 --> 00:40:12,520
Speaker 1: So you give back. Give me an example, how would

764
00:40:12,520 --> 00:40:16,000
Speaker 1: you instruct the machine for the machine learning to give

765
00:40:16,040 --> 00:40:17,879
Speaker 1: you the answer that you want the script? How would

766
00:40:17,920 --> 00:40:18,520
Speaker 1: you instruct it?

767
00:40:19,760 --> 00:40:23,040
Speaker 2: Well, they actually the AI comes up with the challenge itself.

768
00:40:23,640 --> 00:40:25,799
Speaker 2: Instruct your challenge, Well, it just depends on what would

769
00:40:25,840 --> 00:40:28,400
Speaker 2: put in would be create a challenge aligned to the

770
00:40:28,480 --> 00:40:33,359
Speaker 2: United Nations Sustainable Development Goal. Basically choose the goal and

771
00:40:33,600 --> 00:40:35,560
Speaker 2: it relates to food waste, and then it comes out

772
00:40:35,560 --> 00:40:37,399
Speaker 2: and we say, you know, we'll limit it to give

773
00:40:37,480 --> 00:40:38,680
Speaker 2: us two hundred words.

774
00:40:38,440 --> 00:40:41,400
Speaker 1: To Okay, you say the number of words we have it.

775
00:40:41,520 --> 00:40:43,480
Speaker 2: We have a number of things that we would ask.

776
00:40:43,320 --> 00:40:45,840
Speaker 1: How many peop we've got in your place in your organization?

777
00:40:45,920 --> 00:40:50,000
Speaker 2: How many were they're in the room with us. We've

778
00:40:50,000 --> 00:40:54,920
Speaker 2: actually got seven interns, chief operating officer, Marketing manager, Partnerships manager,

779
00:40:56,800 --> 00:40:59,000
Speaker 2: an it person as well.

780
00:40:59,640 --> 00:41:03,640
Speaker 1: Yes, this is pretty this is a I'm getting wrapped now,

781
00:41:03,680 --> 00:41:06,040
Speaker 1: but we're gonna both get wrapped. But this is pretty

782
00:41:06,320 --> 00:41:09,080
Speaker 1: sort of innovative. It's like it's somebody come out of nowhere.

783
00:41:09,840 --> 00:41:12,839
Speaker 1: What I mean, what you're telling me, it's it's it's

784
00:41:14,080 --> 00:41:17,920
Speaker 1: quite for me. I mean I see lots of business ideas,

785
00:41:18,040 --> 00:41:20,959
Speaker 1: but for me, this is sort of quite obverse, something

786
00:41:21,160 --> 00:41:23,680
Speaker 1: I would never think of. Like it's just not many

787
00:41:23,680 --> 00:41:25,839
Speaker 1: people ever think of it. And it's interesting and sort

788
00:41:25,880 --> 00:41:28,399
Speaker 1: of how you went through your process. All the sort

789
00:41:28,440 --> 00:41:30,600
Speaker 1: of things that you did, you sort of plot them

790
00:41:30,640 --> 00:41:33,719
Speaker 1: on a curve and they sort of ended up sort

791
00:41:33,719 --> 00:41:35,640
Speaker 1: of up here somewhere. And if you look at the

792
00:41:35,960 --> 00:41:38,160
Speaker 1: x y AXSS like that you ended up here somehow.

793
00:41:38,960 --> 00:41:42,560
Speaker 1: With this current iteration of all your ideas and all

794
00:41:42,560 --> 00:41:44,480
Speaker 1: your experiences going back right back to when you were

795
00:41:44,520 --> 00:41:49,719
Speaker 1: a little kid, it's quite amazing. Yeah, totally like you're

796
00:41:49,719 --> 00:41:54,000
Speaker 1: giving back now but making money out of it too. People,

797
00:41:54,120 --> 00:41:56,239
Speaker 1: And it's begun for it body. But you said a

798
00:41:56,320 --> 00:42:00,279
Speaker 1: year now, what is the next step for you from here?

799
00:42:00,360 --> 00:42:01,440
Speaker 1: Or is it just more built?

800
00:42:02,440 --> 00:42:06,399
Speaker 2: It's a combination of more built but getting into as

801
00:42:06,400 --> 00:42:10,760
Speaker 2: many classes as we can and helping as many young

802
00:42:11,000 --> 00:42:12,120
Speaker 2: versions of me.

803
00:42:12,160 --> 00:42:14,600
Speaker 1: How many universities or campuses are you on now? So

804
00:42:15,120 --> 00:42:17,000
Speaker 1: per school or per university.

805
00:42:16,600 --> 00:42:19,440
Speaker 2: It's a university. So we formerly partnered with Swinburne University

806
00:42:19,480 --> 00:42:23,400
Speaker 2: of Technology who have been incredible support. They actually provided

807
00:42:23,480 --> 00:42:25,560
Speaker 2: us with funding initially to build out the second version

808
00:42:25,600 --> 00:42:27,640
Speaker 2: of this because I built out the first one myself.

809
00:42:28,280 --> 00:42:31,719
Speaker 2: We didn't talk about that, but so swin burn UNI

810
00:42:32,120 --> 00:42:34,080
Speaker 2: at the moment we're on in Victoria, but we're expanding

811
00:42:34,080 --> 00:42:36,640
Speaker 2: across Australia first before we global.

812
00:42:37,360 --> 00:42:41,759
Speaker 1: Yeah, but you go to the university. Swinburne is more

813
00:42:41,800 --> 00:42:46,200
Speaker 1: on online university, isn't it. I know they are campus

814
00:42:46,480 --> 00:42:48,279
Speaker 1: Yeah yeah, I know them to be quite a big

815
00:42:48,320 --> 00:42:50,280
Speaker 1: online or quite active in the digital environment.

816
00:42:50,360 --> 00:42:55,200
Speaker 2: They are so swinburn MELBOUNI, Melbourne Business School r MIT

817
00:42:55,600 --> 00:42:59,359
Speaker 2: for example. They're all on the platform and they're all yeah, yeah,

818
00:42:59,400 --> 00:43:02,960
Speaker 2: they're all teaching in class.

819
00:43:03,239 --> 00:43:05,680
Speaker 1: That's fantastic. I don't know the name because I don't

820
00:43:05,680 --> 00:43:08,840
Speaker 1: know if when you say it sounds good, solve it?

821
00:43:09,239 --> 00:43:11,160
Speaker 1: But would I would spell it Z O L.

822
00:43:11,239 --> 00:43:12,799
Speaker 2: V I T, but as well I try that, but

823
00:43:12,840 --> 00:43:14,080
Speaker 2: that to my name was already taken.

824
00:43:14,520 --> 00:43:18,000
Speaker 1: Yeah, now that is kind of sexy. It is as cool,

825
00:43:18,000 --> 00:43:19,680
Speaker 1: but as long as you understand it, like I might not.

826
00:43:19,760 --> 00:43:21,359
Speaker 1: If you had said to me, spells it, I would

827
00:43:21,400 --> 00:43:25,160
Speaker 1: have said Z. But maybe if you said wrong, pick

828
00:43:25,160 --> 00:43:26,759
Speaker 1: a first letter, another first thing, I might have come

829
00:43:26,840 --> 00:43:29,839
Speaker 1: up with excess sexy. When you see it, I get it, yeah,

830
00:43:30,400 --> 00:43:33,799
Speaker 1: but like probably instinctively. But now I understand it. Now

831
00:43:33,840 --> 00:43:35,520
Speaker 1: I know why I might. My logic sort of let

832
00:43:35,560 --> 00:43:37,400
Speaker 1: me down that track, and that you've just corrected me.

833
00:43:37,440 --> 00:43:42,759
Speaker 1: That Xavier zero zero, I see when I names it.

834
00:43:42,800 --> 00:43:45,160
Speaker 1: When zero came out, originally I thought myself, I don't

835
00:43:45,160 --> 00:43:46,320
Speaker 1: know if that name is going to stick. But of

836
00:43:46,360 --> 00:43:48,440
Speaker 1: course it's now global business, so don't worry about what

837
00:43:48,520 --> 00:43:50,719
Speaker 1: would I know about how to spell a brand name?

838
00:43:52,560 --> 00:43:56,440
Speaker 1: Do you raise money for this? You for zol like

839
00:43:56,520 --> 00:43:59,960
Speaker 1: as an investors, I feel like you're pitching to me.

840
00:44:00,239 --> 00:44:01,319
Speaker 1: I'm doing what you used to do.

841
00:44:03,760 --> 00:44:07,680
Speaker 2: Yes, so I have angel investors. I have angel investors.

842
00:44:08,120 --> 00:44:11,040
Speaker 1: Yes, and then what's the next stage in terms of

843
00:44:11,880 --> 00:44:15,600
Speaker 1: you know, economies of scale more important. Yes, therefore you

844
00:44:15,640 --> 00:44:18,319
Speaker 1: need more people on the ground and Sydney meln.

845
00:44:19,560 --> 00:44:21,760
Speaker 2: So we'll have to go down the point of properly

846
00:44:21,880 --> 00:44:23,360
Speaker 2: VC at.

847
00:44:23,200 --> 00:44:25,160
Speaker 1: Some stage just a scare you VC.

848
00:44:27,480 --> 00:44:33,239
Speaker 2: Yes and no, mostly yes, but no because it's a

849
00:44:33,280 --> 00:44:38,200
Speaker 2: requirement I think in order to scale properly. And there's

850
00:44:38,239 --> 00:44:41,600
Speaker 2: some amazing angel investor out there that just says, yeah, here,

851
00:44:42,160 --> 00:44:48,440
Speaker 2: here's millions. But yeah, yeah, of course. And also, female

852
00:44:48,680 --> 00:44:53,359
Speaker 2: entrepreneurs are in the minority as far as VC funding.

853
00:44:53,040 --> 00:44:56,760
Speaker 1: Goes, and vcs need to therefore inter their own diversity policies,

854
00:44:56,800 --> 00:44:59,960
Speaker 1: need to actually fund more female entrepreneurs.

855
00:45:00,080 --> 00:45:00,520
Speaker 2: Yeah, they do.

856
00:45:00,800 --> 00:45:02,920
Speaker 1: There's sort of nearly a compulsion to do it. And

857
00:45:03,200 --> 00:45:04,799
Speaker 1: by the ways, plenty of good ones around you don't

858
00:45:04,840 --> 00:45:06,359
Speaker 1: They just don't have to pick someone for the sake

859
00:45:06,400 --> 00:45:08,840
Speaker 1: of it. There's plenty of good female entrepreneurs where they

860
00:45:08,840 --> 00:45:10,960
Speaker 1: can invest. I want to just round off all this

861
00:45:11,080 --> 00:45:21,440
Speaker 1: one thing, Helen Helen Baker today, do you ever encounter

862
00:45:22,760 --> 00:45:32,360
Speaker 1: any negativity today based on your biological origins then factors

863
00:45:32,400 --> 00:45:36,320
Speaker 1: you're female as well, the factor is a female entrepreneur

864
00:45:36,320 --> 00:45:39,360
Speaker 1: as well, a single female, a single female. So do

865
00:45:39,400 --> 00:45:45,759
Speaker 1: you've experience any constraints and or pushback at all that

866
00:45:45,840 --> 00:45:47,760
Speaker 1: would remind you of what it was like when you're.

867
00:45:47,600 --> 00:45:50,680
Speaker 2: A kid, Yeah, all the time.

868
00:45:51,520 --> 00:45:53,479
Speaker 1: And what what would you what would just what would

869
00:45:53,520 --> 00:45:58,960
Speaker 1: you say the most stark reasons as far as you

870
00:45:59,040 --> 00:46:04,839
Speaker 1: can sort of work out for that constraint or for that.

871
00:46:05,239 --> 00:46:09,000
Speaker 2: Pushback that people were giving me.

872
00:46:10,719 --> 00:46:12,640
Speaker 1: Is it because your female is because you're an entrepreneurs,

873
00:46:12,680 --> 00:46:15,919
Speaker 1: because you're female entrepreneurs, because you're a female entrepreneur with

874
00:46:16,480 --> 00:46:18,319
Speaker 1: tan skin, or what is it?

875
00:46:19,800 --> 00:46:23,480
Speaker 2: I don't think it's it's a female entrepreneur with tan skin.

876
00:46:23,600 --> 00:46:28,319
Speaker 2: I think it's in terms of the pushback that I get,

877
00:46:28,480 --> 00:46:33,440
Speaker 2: it's mostly I think related to you don't have enough

878
00:46:33,440 --> 00:46:36,359
Speaker 2: traction yet. But when it comes to funding for example, Yeah,

879
00:46:37,120 --> 00:46:39,799
Speaker 2: for example, yeah, yeah, that's right, you don't have enough tracks.

880
00:46:39,880 --> 00:46:41,960
Speaker 1: Where's your first million bucks? Where's your first me in

881
00:46:42,000 --> 00:46:42,439
Speaker 1: doors proper?

882
00:46:42,680 --> 00:46:47,640
Speaker 2: Yeah? Yeah. But in relation to other pushback, and I

883
00:46:47,680 --> 00:46:52,160
Speaker 2: think it's just standard sales. Yeah, it's just picking up

884
00:46:52,160 --> 00:46:54,759
Speaker 2: the phone to people and trying to sell selling and

885
00:46:55,360 --> 00:46:56,520
Speaker 2: you get pushed back all the time.

886
00:46:57,120 --> 00:46:58,759
Speaker 1: And how do you deal with that? Do you give

887
00:46:58,760 --> 00:47:00,839
Speaker 1: a shit? Like do you just see move on? Who cares?

888
00:47:00,920 --> 00:47:03,520
Speaker 2: You? Just move on? And do you.

889
00:47:03,600 --> 00:47:09,839
Speaker 1: Employ people of let's call it, of diverse backgrounds in

890
00:47:09,880 --> 00:47:14,160
Speaker 1: your business in order to make sure that everyone has.

891
00:47:14,080 --> 00:47:18,919
Speaker 2: A chance, not just because everyone has a chance. But

892
00:47:19,120 --> 00:47:22,640
Speaker 2: of course diversity is really important to me, absolutely, but

893
00:47:22,680 --> 00:47:25,120
Speaker 2: they need to have the skills and the talent and

894
00:47:25,840 --> 00:47:27,440
Speaker 2: the right fit as well.

895
00:47:27,520 --> 00:47:28,839
Speaker 1: So where do you draw the line on that? So

896
00:47:29,000 --> 00:47:30,879
Speaker 1: how do you do that? How do you balance that up?

897
00:47:31,560 --> 00:47:38,080
Speaker 1: Make sure you've got enough diversity both gender, sex, nationality, ethnicity,

898
00:47:38,239 --> 00:47:41,799
Speaker 1: et cetera. How do you build a balance or is

899
00:47:41,800 --> 00:47:46,200
Speaker 1: it just a constant moving target between that and skills

900
00:47:47,239 --> 00:47:51,160
Speaker 1: and not overdoing it and say too many females because

901
00:47:51,160 --> 00:47:53,359
Speaker 1: obvius you might not have enough males. I'm like, how

902
00:47:53,400 --> 00:47:53,640
Speaker 1: do you?

903
00:47:54,400 --> 00:47:56,359
Speaker 2: I think you just get the best person for the job.

904
00:47:56,840 --> 00:48:01,200
Speaker 1: Yeah, that's interesting coming from someone like you. That's very interesting.

905
00:48:01,200 --> 00:48:03,120
Speaker 1: The best person for the job, best person for the

906
00:48:03,239 --> 00:48:05,920
Speaker 1: job without any prejudices though of course you do not

907
00:48:05,960 --> 00:48:08,800
Speaker 1: have any prejudice against the It's probably impossible for you

908
00:48:08,840 --> 00:48:09,480
Speaker 1: to have a prejudice it.

909
00:48:09,640 --> 00:48:11,920
Speaker 2: You know what is interesting about this mark is it

910
00:48:12,360 --> 00:48:15,720
Speaker 2: often what I'm seeing, particularly in terms of those people

911
00:48:15,760 --> 00:48:19,520
Speaker 2: who come through the zolvet platform who really want these

912
00:48:19,560 --> 00:48:24,320
Speaker 2: opportunities are people like myself who've been dissed as students,

913
00:48:24,320 --> 00:48:28,719
Speaker 2: as in students who've had disadvantage backgrounds and who are

914
00:48:28,719 --> 00:48:31,200
Speaker 2: trying to get ahead and that this is their way

915
00:48:31,760 --> 00:48:36,400
Speaker 2: to really demonstrate that they're prepared to go the extra mile.

916
00:48:36,680 --> 00:48:41,200
Speaker 2: And often it's international students, so that is really interesting.

917
00:48:42,080 --> 00:48:44,000
Speaker 1: Do you think, as you have to wind up here,

918
00:48:44,000 --> 00:48:45,920
Speaker 1: but I'm always fascinated about this, do you think that's

919
00:48:45,960 --> 00:48:52,239
Speaker 1: as a result of our non international students have it

920
00:48:52,239 --> 00:48:55,880
Speaker 1: too good and there's no compulsion, there's no need for

921
00:48:55,920 --> 00:48:57,680
Speaker 1: them to really put themselves out there.

922
00:48:58,360 --> 00:49:02,480
Speaker 2: I think Australians very privileged. I think Australian.

923
00:49:02,040 --> 00:49:04,320
Speaker 1: Students relative to non Australians.

924
00:49:04,360 --> 00:49:08,920
Speaker 2: Yep, yes, I believe. So. I also believe and this

925
00:49:10,200 --> 00:49:17,800
Speaker 2: racism is still ethnic discrimination still exists. And Monash for example,

926
00:49:17,800 --> 00:49:21,359
Speaker 2: put out a study recently which proved is quite well

927
00:49:21,400 --> 00:49:24,640
Speaker 2: in the workplace. They did a study of two year

928
00:49:24,680 --> 00:49:27,759
Speaker 2: study with twelve thousand applicants. They put applications out there.

929
00:49:27,760 --> 00:49:32,560
Speaker 2: They had English sounding names and you know, ethnic sounding names,

930
00:49:32,960 --> 00:49:38,600
Speaker 2: and those with ethnic sounding names received fewer callbacks compared

931
00:49:38,600 --> 00:49:40,920
Speaker 2: to the English and they had identical safees.

932
00:49:42,200 --> 00:49:45,520
Speaker 1: So you know, I'm sorry, I just do not get

933
00:49:45,920 --> 00:49:49,680
Speaker 1: why there should be any prejudice against a person because

934
00:49:49,719 --> 00:49:52,440
Speaker 1: of whether oborn, what kind of their eyes and skin are,

935
00:49:52,880 --> 00:49:55,880
Speaker 1: or their hair, what their culture is, what the religion is.

936
00:49:55,920 --> 00:49:56,520
Speaker 2: I just don't.

937
00:49:56,400 --> 00:49:59,400
Speaker 1: Understand how they can make any difference in relation to

938
00:50:00,160 --> 00:50:01,359
Speaker 1: hiring a person at all.

939
00:50:01,760 --> 00:50:03,720
Speaker 2: Well, that is a lovelyad here.

940
00:50:03,680 --> 00:50:05,919
Speaker 1: No, but I grew up that way. But like, how

941
00:50:05,960 --> 00:50:10,960
Speaker 1: can anybody. I don't care if you're black from Middle

942
00:50:10,960 --> 00:50:13,920
Speaker 1: of Africa, the Congo wherever, if you have got the skills,

943
00:50:14,160 --> 00:50:16,239
Speaker 1: But I don't see what that individual's different. But the

944
00:50:16,280 --> 00:50:18,200
Speaker 1: difference is that particular individual because of the color of

945
00:50:18,239 --> 00:50:19,120
Speaker 1: the skin, for example.

946
00:50:19,320 --> 00:50:21,840
Speaker 2: But it goes back, it goes back to history and

947
00:50:22,880 --> 00:50:26,080
Speaker 2: back to the nineteen oh one. These I know, but

948
00:50:26,160 --> 00:50:28,600
Speaker 2: it's still ingrained in culture today.

949
00:50:29,280 --> 00:50:33,120
Speaker 1: Even if you grow up that way, surely you're an

950
00:50:33,160 --> 00:50:35,200
Speaker 1: intellect will tell you there is no difference.

951
00:50:36,560 --> 00:50:38,279
Speaker 2: Do you know what I love about this gen that

952
00:50:38,320 --> 00:50:43,760
Speaker 2: the next generations though, they embrace diversity like no other generation,

953
00:50:44,040 --> 00:50:45,640
Speaker 2: which I absolutely love.

954
00:50:46,080 --> 00:50:48,160
Speaker 1: Well, do you think there's mull? Just have finished off

955
00:50:48,239 --> 00:50:49,840
Speaker 1: this sory because I'm getting wound up. But do you

956
00:50:49,880 --> 00:50:53,200
Speaker 1: think there's any difference between Like in my case, I

957
00:50:53,280 --> 00:50:56,480
Speaker 1: just don't see any difference between aywheys so yep as

958
00:50:56,480 --> 00:50:59,120
Speaker 1: opposed to I don't go out and embrace diversity and say, oh,

959
00:50:59,200 --> 00:51:02,640
Speaker 1: I ain't going to go get an African person who

960
00:51:02,680 --> 00:51:04,080
Speaker 1: work in my place and I we're going to get

961
00:51:04,120 --> 00:51:07,560
Speaker 1: a that's just for it.

962
00:51:07,600 --> 00:51:08,759
Speaker 2: There's a lot of that going on.

963
00:51:08,840 --> 00:51:11,399
Speaker 1: Do you think there's any difference between actually embracing it

964
00:51:11,680 --> 00:51:14,000
Speaker 1: as a young person, say a gen Z person who

965
00:51:14,080 --> 00:51:19,200
Speaker 1: actually is sort of passionate about it, as opposed to

966
00:51:19,280 --> 00:51:21,520
Speaker 1: say someone like me, which I think I think there's

967
00:51:21,520 --> 00:51:23,560
Speaker 1: a lot of people around like me, but obviously never

968
00:51:24,000 --> 00:51:27,880
Speaker 1: that's in terms of sovis that's the end of one,

969
00:51:28,800 --> 00:51:31,640
Speaker 1: which is not Brett good so very statistically speaking I'm

970
00:51:31,640 --> 00:51:35,359
Speaker 1: talking about. But where I think I just don't think

971
00:51:35,360 --> 00:51:38,120
Speaker 1: it's any different. So between anybody. I don't care what

972
00:51:38,160 --> 00:51:40,040
Speaker 1: you look like or which part of the worlds you're

973
00:51:40,040 --> 00:51:42,000
Speaker 1: born and born and even where your book are brought up.

974
00:51:42,000 --> 00:51:44,000
Speaker 1: I couldn't care less if you've got the skill and

975
00:51:44,040 --> 00:51:46,120
Speaker 1: you've got the energy and whatever, you've got the job

976
00:51:46,440 --> 00:51:49,520
Speaker 1: in my case, And is there any difference between the

977
00:51:49,560 --> 00:51:53,040
Speaker 1: way I feel and gen Z who actually embraces it like,

978
00:51:53,160 --> 00:51:55,399
Speaker 1: actually it's a thing for them, it's not a thing

979
00:51:55,400 --> 00:51:57,719
Speaker 1: for me. But I also prejudice is not a thing

980
00:51:57,719 --> 00:52:00,480
Speaker 1: for me either, not either one? Is it a difference

981
00:52:00,480 --> 00:52:03,759
Speaker 1: because I'm only just thought of this now and you're

982
00:52:03,800 --> 00:52:05,120
Speaker 1: someone who's in the middle of it all this, so

983
00:52:05,320 --> 00:52:07,280
Speaker 1: maybe you can help me out here. Is there a difference?

984
00:52:07,440 --> 00:52:09,719
Speaker 1: Should I be actually embracing it like the gen Z

985
00:52:10,600 --> 00:52:13,239
Speaker 1: am I letting anyone down by not embracing it, given

986
00:52:13,280 --> 00:52:16,640
Speaker 1: that I don't have any prejudice whatsoever prejudicial bone in

987
00:52:16,680 --> 00:52:20,719
Speaker 1: my body? Should I be changing it up and embracing

988
00:52:20,760 --> 00:52:21,360
Speaker 1: it like gen Z?

989
00:52:21,600 --> 00:52:22,440
Speaker 2: How would you do that?

990
00:52:22,480 --> 00:52:25,880
Speaker 1: I don't know. That's my second question to you, when

991
00:52:25,920 --> 00:52:26,960
Speaker 1: I was going to say how do I do it?

992
00:52:26,960 --> 00:52:28,000
Speaker 1: But yeah, how would.

993
00:52:27,840 --> 00:52:30,840
Speaker 2: You embrace it? I guess you have you have a

994
00:52:30,880 --> 00:52:34,480
Speaker 2: platform that you can embrace it in that way.

995
00:52:35,160 --> 00:52:35,880
Speaker 1: I could promote it.

996
00:52:35,960 --> 00:52:37,799
Speaker 2: Yeah, yeah, you could promote it, but you could also

997
00:52:37,840 --> 00:52:38,959
Speaker 2: embrace it in Is there.

998
00:52:38,880 --> 00:52:40,960
Speaker 1: A reason why I need to do that? I mean,

999
00:52:41,280 --> 00:52:43,200
Speaker 1: I'm not asking for a judgment a bit, like just

1000
00:52:43,200 --> 00:52:46,000
Speaker 1: just help me out it, Like is your industries what

1001
00:52:46,200 --> 00:52:49,520
Speaker 1: you do? And you're somewhere in between me and those

1002
00:52:49,600 --> 00:52:52,080
Speaker 1: gen zs closer to gen Z than you ask to me,

1003
00:52:53,160 --> 00:52:55,759
Speaker 1: but like it, just help me out it, Like is

1004
00:52:55,760 --> 00:53:00,319
Speaker 1: there something that I'm missing that I'm not doing as

1005
00:53:00,320 --> 00:53:04,839
Speaker 1: an old dude.

1006
00:53:04,400 --> 00:53:06,279
Speaker 2: Something that you're missing, that you're not doing well.

1007
00:53:06,640 --> 00:53:09,520
Speaker 1: I think should be saying, all my team and okay,

1008
00:53:09,600 --> 00:53:13,120
Speaker 1: let's from now on, we're going to have two more girls,

1009
00:53:13,280 --> 00:53:14,960
Speaker 1: and we're going to get.

1010
00:53:15,160 --> 00:53:18,319
Speaker 2: The best way. And one you don't want to do

1011
00:53:18,360 --> 00:53:21,879
Speaker 2: something just for the sake of it, which is washing.

1012
00:53:22,160 --> 00:53:24,840
Speaker 2: But the best way I think that you can embrace

1013
00:53:25,400 --> 00:53:29,240
Speaker 2: this is by leading by example. So it's by the smallest,

1014
00:53:29,320 --> 00:53:34,480
Speaker 2: it's the little one percent. It's the treating people you

1015
00:53:34,520 --> 00:53:37,479
Speaker 2: know in a cafe who just exactly how you would

1016
00:53:37,480 --> 00:53:41,399
Speaker 2: treat anyone, but exactly anything you do anyway, So you're

1017
00:53:41,440 --> 00:53:42,360
Speaker 2: already embracing it.

1018
00:53:42,520 --> 00:53:43,759
Speaker 1: Okay, that's enough.

1019
00:53:44,520 --> 00:53:48,680
Speaker 2: Students, don't you know young gen Z for example, sometimes

1020
00:53:48,680 --> 00:53:50,520
Speaker 2: they go a little bit too far.

1021
00:53:51,400 --> 00:53:54,480
Speaker 1: Yeah, yeah, yeah, That's sort of my point because something

1022
00:53:54,560 --> 00:53:57,120
Speaker 1: I'm wondering if I think that's where you if I'm

1023
00:53:57,160 --> 00:54:01,040
Speaker 1: out of touch, and because I've always thought this way,

1024
00:54:02,200 --> 00:54:04,359
Speaker 1: I couldn't care less where someone comes from. Like I said,

1025
00:54:04,360 --> 00:54:07,440
Speaker 1: that Chinese kid Michael him like he was like I

1026
00:54:07,480 --> 00:54:10,319
Speaker 1: was an order of the guy, Like I didn't even

1027
00:54:10,520 --> 00:54:12,440
Speaker 1: sort of I mean, obviously he looked different everybody else,

1028
00:54:12,480 --> 00:54:16,040
Speaker 1: but I meant nothing to me. Yeah, I actually felt

1029
00:54:16,080 --> 00:54:17,960
Speaker 1: like you looked a bit, like, in a good way,

1030
00:54:17,960 --> 00:54:20,880
Speaker 1: exotic relative to all of us. You know, I look

1031
00:54:21,000 --> 00:54:23,239
Speaker 1: like a typical European and all my friends look like

1032
00:54:23,280 --> 00:54:27,760
Speaker 1: typical Australians. He was like, yeah, he was. He looked exotic,

1033
00:54:28,200 --> 00:54:30,520
Speaker 1: like he looked cool. It was cool, looked like him.

1034
00:54:30,880 --> 00:54:32,799
Speaker 1: Like girls like you, Like if you went to my

1035
00:54:32,880 --> 00:54:35,319
Speaker 1: school or the girls school next door to me, the

1036
00:54:35,360 --> 00:54:38,000
Speaker 1: boys would have thought you looked exotic relative to all

1037
00:54:38,040 --> 00:54:39,960
Speaker 1: the other girls. I think I don't know, maybe I'm.

1038
00:54:39,840 --> 00:54:43,480
Speaker 2: Just do you think I think a lot of boys.

1039
00:54:43,560 --> 00:54:44,279
Speaker 1: Yeah, I'm not sure.

1040
00:54:44,320 --> 00:54:47,200
Speaker 2: I'm just saying you're coming from your friend, Yeah, yeah,

1041
00:54:47,360 --> 00:54:48,040
Speaker 2: I just lovely.

1042
00:54:48,120 --> 00:54:50,239
Speaker 1: Yeah, I don't know, but like I'm just thinking that's

1043
00:54:50,280 --> 00:54:52,880
Speaker 1: what they would have thought. But maybe they didn't. But

1044
00:54:53,160 --> 00:54:55,800
Speaker 1: because and because I think what's really important is always

1045
00:54:55,800 --> 00:54:58,520
Speaker 1: to keep evolving and from where you are, where you

1046
00:54:58,800 --> 00:55:01,080
Speaker 1: and where you've evolved, it just to continue to evolve,

1047
00:55:01,120 --> 00:55:04,440
Speaker 1: because I think in terms of relevancy, you must evolve.

1048
00:55:05,160 --> 00:55:08,600
Speaker 1: And and you know, gen Z is a really mysterious,

1049
00:55:08,760 --> 00:55:15,439
Speaker 1: mysterious place for me, and I'm always trying to stay modern. Yeah, yeah,

1050
00:55:15,480 --> 00:55:17,160
Speaker 1: because I think it keeps you, It keeps you keeps

1051
00:55:17,200 --> 00:55:19,640
Speaker 1: you young, keeps you young great, and if you don't,

1052
00:55:20,040 --> 00:55:24,800
Speaker 1: you can sort of slump back into a pretty shitty place,

1053
00:55:24,840 --> 00:55:27,799
Speaker 1: and then you start to age my view, and.

1054
00:55:28,520 --> 00:55:30,680
Speaker 2: You need to surround yourself with young people too. And

1055
00:55:30,719 --> 00:55:33,600
Speaker 2: that's why I love like I've got eight interns at

1056
00:55:33,600 --> 00:55:36,560
Speaker 2: the moment, and they're young and enthusiastic and they keep

1057
00:55:36,600 --> 00:55:38,080
Speaker 2: me young. They're great.

1058
00:55:38,360 --> 00:55:42,680
Speaker 1: It's worked. Thanks good luck to you. Thanks very much, Ellen.

1059
00:55:42,800 --> 00:56:01,360
Speaker 1: Great talking to you got me thinking great.