WEBVTT 1 00:00:00.451 --> 00:00:01.284 (calm music) 2 00:00:01.284 --> 00:00:02.950 Ethical use of technology is 3 00:00:02.950 --> 00:00:05.910 and should be a concern for organizations everywhere, 4 00:00:05.910 --> 00:00:07.800 but it's complicated. 5 00:00:07.800 --> 00:00:10.170 Today we talk with Elizabeth Renieris, 6 00:00:10.170 --> 00:00:11.060 Founding Director of 7 00:00:11.060 --> 00:00:13.830 the Notre Dame IBM Technology Ethics Lab, 8 00:00:13.830 --> 00:00:15.940 about what organizations can do today 9 00:00:15.940 --> 00:00:17.890 without waiting for the perfect answer. 10 00:00:19.900 --> 00:00:21.430 Welcome to Me, Myself, and AI, 11 00:00:21.430 --> 00:00:24.630 a podcast on artificial intelligence in business. 12 00:00:24.630 --> 00:00:28.480 Each episode we introduce you to someone innovating with AI. 13 00:00:28.480 --> 00:00:30.980 I'm Sam Ramsbotham, Professor of Information Systems 14 00:00:30.980 --> 00:00:33.000 at Boston College. 15 00:00:33.000 --> 00:00:34.700 I'm also the guest editor for the 16 00:00:34.700 --> 00:00:37.310 AI and Business Strategy Big Idea program 17 00:00:37.310 --> 00:00:40.100 at MIT Sloan Management Review. 18 00:00:40.100 --> 00:00:42.270 And I'm Shervin Khodabandeh, 19 00:00:42.270 --> 00:00:43.980 Senior Partner with BCG 20 00:00:43.980 --> 00:00:47.790 and I co-lead BCG's AI practice in North America 21 00:00:47.790 --> 00:00:51.870 and together MIT SMR and BCG have been researching AI 22 00:00:51.870 --> 00:00:55.166 for five years, interviewing hundreds of practitioners, 23 00:00:55.166 --> 00:00:58.200 and surveying thousands of companies on what it takes 24 00:00:58.200 --> 00:01:02.120 to build and to deploy and scale AI capabilities 25 00:01:02.120 --> 00:01:03.500 across the organization 26 00:01:03.500 --> 00:01:06.053 and really transform the way organizations operate. 27 00:01:08.680 --> 00:01:10.530 Today we're talking with Elizabeth Renieris. 28 00:01:10.530 --> 00:01:12.550 Elizabeth is the Founding Director 29 00:01:12.550 --> 00:01:15.418 of the Notre Dame IBM Technology Ethics Lab 30 00:01:15.418 --> 00:01:18.670 as well as founder and CEO of HACKYLAWYER. 31 00:01:18.670 --> 00:01:20.700 Elizabeth, thanks for taking the time to talk with us today. 32 00:01:20.700 --> 00:01:21.533 Welcome. 33 00:01:21.533 --> 00:01:22.930 Thanks for having me. 34 00:01:22.930 --> 00:01:24.560 Let's start with your current role, 35 00:01:24.560 --> 00:01:27.933 your current new role at the Notre Dame IBM. 36 00:01:27.933 --> 00:01:28.958 I was going to ask which one? 37 00:01:28.958 --> 00:01:30.340 (all laughing) 38 00:01:30.340 --> 00:01:33.450 Well, I was thinking about the ethics lab 39 00:01:33.450 --> 00:01:36.450 but you actually can start with whatever you like. 40 00:01:36.450 --> 00:01:38.530 Sure, so as you mentioned, 41 00:01:38.530 --> 00:01:40.879 I've been recently appointed as the Founding Director 42 00:01:40.879 --> 00:01:43.329 of a new technology ethics lab 43 00:01:43.329 --> 00:01:46.038 at the University of Notre Dame. 44 00:01:46.038 --> 00:01:47.430 It's actually called 45 00:01:47.430 --> 00:01:49.750 the Notre Dame IBM Technology Ethics Lab 46 00:01:49.750 --> 00:01:52.186 as the generous seed funding is actually from IBM. 47 00:01:52.186 --> 00:01:55.170 My appointment is a faculty appointment with 48 00:01:55.170 --> 00:01:58.560 the University of Notre Dame and the intention of the lab 49 00:01:58.560 --> 00:02:00.550 is to compliment Notre Dame's existing 50 00:02:00.550 --> 00:02:04.730 Technology Ethics Center which is a very traditional 51 00:02:04.730 --> 00:02:07.123 academic research center focused on technology ethics. 52 00:02:07.123 --> 00:02:10.670 So you can imagine there are many tenured faculty members 53 00:02:10.670 --> 00:02:12.530 affiliated with the center and they produce sort 54 00:02:12.530 --> 00:02:14.150 of traditional academic research, 55 00:02:14.150 --> 00:02:15.970 peer-previewed journal articles. 56 00:02:15.970 --> 00:02:19.210 The lab in contrast to that is meant to focus 57 00:02:19.210 --> 00:02:21.580 on practitioner-oriented artifacts. 58 00:02:21.580 --> 00:02:23.525 So the things that we want to produce are 59 00:02:23.525 --> 00:02:27.150 for audiences that include companies themselves, 60 00:02:27.150 --> 00:02:29.350 but also for law and policy makers, 61 00:02:29.350 --> 00:02:32.400 also for civil society and other stakeholders. 62 00:02:32.400 --> 00:02:35.130 And we want them to be very tangible and very practical. 63 00:02:35.130 --> 00:02:37.085 So we're looking to produce things like 64 00:02:37.085 --> 00:02:39.746 open source tool kits, and model legislation, 65 00:02:39.746 --> 00:02:43.230 and explainer videos, and model audits, 66 00:02:43.230 --> 00:02:45.240 and a whole array of things that 67 00:02:45.240 --> 00:02:47.570 you wouldn't necessarily find from a traditional 68 00:02:47.570 --> 00:02:49.470 academic research center. 69 00:02:49.470 --> 00:02:52.460 What we really need in this space is we need centers 70 00:02:52.460 --> 00:02:54.130 and institutions that can translate 71 00:02:54.130 --> 00:02:56.360 between academia and practice. 72 00:02:56.360 --> 00:02:58.850 The beauty of housing the lab in the university 73 00:02:58.850 --> 00:03:01.070 of course is having access to the faculty 74 00:03:01.070 --> 00:03:02.560 that's generating the scholarship 75 00:03:02.560 --> 00:03:04.810 and the theoretical foundations for the work. 76 00:03:05.665 --> 00:03:06.498 Can you comment a bit more 77 00:03:06.498 --> 00:03:08.100 on how you guys make that happen? 78 00:03:08.100 --> 00:03:10.750 Because I know there's a lot of primary research 79 00:03:10.750 --> 00:03:13.360 and then you have the faculty's point of view, 80 00:03:13.360 --> 00:03:16.580 and I assume that there's also industry connections 81 00:03:16.580 --> 00:03:21.330 and some of these applications in real life come in to play, 82 00:03:21.330 --> 00:03:22.908 which is really important as you say. 83 00:03:22.908 --> 00:03:26.610 What are some of the ways you guys enable that? 84 00:03:26.610 --> 00:03:28.550 Right now as we're getting up and running, 85 00:03:28.550 --> 00:03:30.840 really what we're focusing on is convening power. 86 00:03:30.840 --> 00:03:33.330 So we're looking to convene groups of people 87 00:03:33.330 --> 00:03:35.170 who aren't necessarily talking to each other 88 00:03:35.170 --> 00:03:36.530 and to do a lot of that translation work. 89 00:03:36.530 --> 00:03:41.270 So right now the intention is to put out 90 00:03:41.270 --> 00:03:43.970 an official call for proposals to the general public 91 00:03:43.970 --> 00:03:46.730 and to be sourcing projects from all the different 92 00:03:46.730 --> 00:03:49.820 stakeholders that I outlined consisting of teams 93 00:03:49.820 --> 00:03:52.510 of individuals who come from different industries 94 00:03:52.510 --> 00:03:56.500 and sectors and represent different sectors of society. 95 00:03:56.500 --> 00:03:59.300 And to have them focus on projects that actually try 96 00:03:59.300 --> 00:04:00.710 and solve real-world challenges. 97 00:04:00.710 --> 00:04:03.560 So for example, right now during the pandemic, 98 00:04:03.560 --> 00:04:04.860 those challenges might be something 99 00:04:04.860 --> 00:04:07.362 like returning to work or returning to school. 100 00:04:07.362 --> 00:04:08.860 And then of course, 101 00:04:08.860 --> 00:04:10.740 what we want to do as the lab is we want to 102 00:04:10.740 --> 00:04:13.260 take the brilliant work that the faculty 103 00:04:13.260 --> 00:04:15.783 at Notre Dame is doing, and eventually elsewhere, 104 00:04:15.783 --> 00:04:18.413 and leverage that to sort of underpin 105 00:04:18.413 --> 00:04:22.040 and to inform the actual projects that we're sourcing. 106 00:04:22.040 --> 00:04:24.480 And we can hopefully build some kind of narrative arc 107 00:04:24.480 --> 00:04:27.870 around how you start translating that theory into practice. 108 00:04:27.870 --> 00:04:30.550 It seems like you're looking at ethics in AI 109 00:04:30.550 --> 00:04:32.420 from two sides, right? 110 00:04:32.420 --> 00:04:35.563 One is the ethics of the technology itself, 111 00:04:35.563 --> 00:04:39.357 as in, is what the technology doing ethical 112 00:04:39.357 --> 00:04:41.830 and how do you make sure it is ethical 113 00:04:43.207 --> 00:04:47.607 and how can technology help the ethics conversation itself? 114 00:04:48.478 --> 00:04:49.970 I think it's absolutely both. 115 00:04:49.970 --> 00:04:52.190 In my mind, you cannot separate 116 00:04:52.190 --> 00:04:53.700 a conversation about technology ethics 117 00:04:53.700 --> 00:04:55.790 from a conversation about values, 118 00:04:55.790 --> 00:04:58.820 both individual values and collective societal values. 119 00:04:58.820 --> 00:05:01.270 So what I find really fascinating about this space 120 00:05:01.270 --> 00:05:03.340 is that you're right, while we're looking at the 121 00:05:03.340 --> 00:05:05.977 ethical challenges presented by specific technologies, 122 00:05:05.977 --> 00:05:08.498 we're also then confronted with having to identify 123 00:05:08.498 --> 00:05:12.156 and prioritize and reconcile competing values 124 00:05:12.156 --> 00:05:14.450 of different people and communities 125 00:05:14.450 --> 00:05:16.530 and stakeholders in the conversation. 126 00:05:16.530 --> 00:05:18.990 And you know, when we have a specific challenge 127 00:05:18.990 --> 00:05:21.150 or a specific technology, it actually really turns 128 00:05:21.150 --> 00:05:24.160 the mirror back on us as a society and forces us 129 00:05:24.160 --> 00:05:26.880 to ask the question of what kind of society do we want to be 130 00:05:26.880 --> 00:05:28.410 or what kind of company do we want to be, 131 00:05:28.410 --> 00:05:30.954 or what kind of you know, individual 132 00:05:30.954 --> 00:05:31.787 or researcher do we want to be 133 00:05:31.787 --> 00:05:33.703 and what are our values and how do those values align 134 00:05:33.703 --> 00:05:35.370 with what it is that we're working on 135 00:05:35.370 --> 00:05:36.700 from a technology standpoint? 136 00:05:36.700 --> 00:05:39.360 So I believe it's absolutely both. 137 00:05:39.360 --> 00:05:41.320 And I think that's also been part of the evolution 138 00:05:41.320 --> 00:05:44.020 of the ethics conversation in the last couple of years 139 00:05:44.020 --> 00:05:46.510 is that while perhaps it started out with the lens very 140 00:05:46.510 --> 00:05:49.300 much on the technology, it's been very much turned around 141 00:05:49.300 --> 00:05:51.670 and focused on, you know, who's building it? 142 00:05:51.670 --> 00:05:53.710 Who's at the table, what's the conversation? 143 00:05:53.710 --> 00:05:54.850 What are the parameters? 144 00:05:54.850 --> 00:05:55.750 What do we count? 145 00:05:55.750 --> 00:05:57.210 What values matter? 146 00:05:57.210 --> 00:05:59.660 And actually from my standpoint, those are the really 147 00:05:59.660 --> 00:06:02.150 important questions that hopefully technology 148 00:06:02.150 --> 00:06:05.390 is an entry point for us to discuss. 149 00:06:05.390 --> 00:06:06.820 Sam, I was just going to ask Elizabeth 150 00:06:06.820 --> 00:06:09.880 to maybe share with us how she ended up here, 151 00:06:09.880 --> 00:06:11.127 like the path that you took, that- 152 00:06:11.127 --> 00:06:12.944 -How much time do you have? 153 00:06:12.944 --> 00:06:13.777 (all laughing) 154 00:06:13.777 --> 00:06:15.050 I'll give you the abbreviated version. 155 00:06:15.050 --> 00:06:18.262 So I was classmates with Mark Zuckerberg at Harvard 156 00:06:18.262 --> 00:06:21.902 and I've been thinking about these issues ever since. 157 00:06:21.902 --> 00:06:23.980 But more seriously, 158 00:06:23.980 --> 00:06:26.600 my sort of professional trajectory was that 159 00:06:26.600 --> 00:06:27.650 after law school, 160 00:06:27.650 --> 00:06:30.020 I worked at Department of Homeland Security 161 00:06:30.020 --> 00:06:33.241 for a couple of years in their General Counsel's office. 162 00:06:33.241 --> 00:06:34.904 And this was a long time after 9/11, 163 00:06:34.904 --> 00:06:37.010 and I actually am from New York 164 00:06:37.010 --> 00:06:39.340 and have vivid memories of the event. 165 00:06:39.340 --> 00:06:42.110 And I was really struck by how much 166 00:06:42.110 --> 00:06:45.576 of the emergency infrastructure was still in place 167 00:06:45.576 --> 00:06:50.200 more than a decade after it was initially rolled out. 168 00:06:50.200 --> 00:06:54.555 And I subsequently went back to obtain an LLM in London 169 00:06:54.555 --> 00:06:58.400 and accidentally having arrived in the year 2012, 170 00:06:58.400 --> 00:06:59.970 started working on the first draft 171 00:06:59.970 --> 00:07:02.120 of what became the General Data Protection Regulation 172 00:07:02.120 --> 00:07:03.650 or the GDPR. 173 00:07:03.650 --> 00:07:05.940 And through that process gained a lot of exposure 174 00:07:05.940 --> 00:07:10.070 to the ad tech industry, the FinTech industry, 175 00:07:10.070 --> 00:07:12.375 somewhere along the way read the Bitcoin white paper, 176 00:07:12.375 --> 00:07:14.520 came back to the states 177 00:07:14.520 --> 00:07:16.420 just before the referendum, and was branded 178 00:07:16.420 --> 00:07:17.320 a blockchain lawyer 179 00:07:17.320 --> 00:07:19.428 because I had read the Bitcoin white paper. 180 00:07:19.428 --> 00:07:21.349 (all laughing) 181 00:07:21.349 --> 00:07:23.180 So then I had this interesting dance 182 00:07:23.180 --> 00:07:25.440 in trying to be a data protection and privacy lawyer 183 00:07:25.440 --> 00:07:27.440 and also, you know, split my time 184 00:07:27.440 --> 00:07:29.648 with the sort of blockchain distributed ledger folks. 185 00:07:29.648 --> 00:07:32.480 And I quickly picked up on some of the unsavory, 186 00:07:32.480 --> 00:07:36.210 unethical behavior that I saw in the space 187 00:07:36.210 --> 00:07:37.680 and I was really bothered by it 188 00:07:37.680 --> 00:07:40.320 and it also sort of triggered these memories 189 00:07:40.320 --> 00:07:41.970 of the experience with Mark Zuckerberg 190 00:07:41.970 --> 00:07:44.340 scraping faces of my classmates in university. 191 00:07:44.340 --> 00:07:46.480 And it was just an interesting thing that 192 00:07:46.480 --> 00:07:48.240 I didn't appreciate at the time 193 00:07:48.240 --> 00:07:50.320 but sort of bubbled in the background. 194 00:07:50.320 --> 00:07:51.650 And that led me to actually work 195 00:07:51.650 --> 00:07:53.613 in-house at a couple of companies' 196 00:07:53.613 --> 00:07:56.221 startups based in Silicon Valley and elsewhere. 197 00:07:56.221 --> 00:07:58.940 And there was more of this sort of unsavory behavior. 198 00:07:58.940 --> 00:08:01.500 And I thought if only we could talk about technology 199 00:08:01.500 --> 00:08:04.120 we can engage with technology and be excited about it 200 00:08:04.120 --> 00:08:07.190 without all of these terrible downsides. 201 00:08:07.190 --> 00:08:09.240 I think part of the reason I was observing that 202 00:08:09.240 --> 00:08:11.220 is because you didn't have the right people in the room. 203 00:08:11.220 --> 00:08:13.580 So you had technologists that were talking 204 00:08:13.580 --> 00:08:15.910 past and over lawyers and policy makers. 205 00:08:15.910 --> 00:08:19.300 And that was my idea in late 2017 206 00:08:19.300 --> 00:08:21.440 to start my HACKYLAWYER consultancy. 207 00:08:21.440 --> 00:08:23.840 And the idea with that was, you know 208 00:08:23.840 --> 00:08:25.270 I'm fairly technically savvy 209 00:08:25.270 --> 00:08:27.760 but I have this great training, these legal skills, 210 00:08:27.760 --> 00:08:29.160 these public policy skills. 211 00:08:29.160 --> 00:08:31.510 I'd like to be able to translate across those groups 212 00:08:31.510 --> 00:08:33.500 and bring them together and 213 00:08:33.500 --> 00:08:35.870 built up a pretty successful consultancy 214 00:08:35.870 --> 00:08:38.120 around that for a couple of years thereafter. 215 00:08:38.960 --> 00:08:41.870 That's a very inspiring story from the beginning 216 00:08:41.870 --> 00:08:43.350 to here. 217 00:08:43.350 --> 00:08:44.870 Kind of want to ask about the long version, 218 00:08:44.870 --> 00:08:46.533 but I don't know that we have time for that. 219 00:08:46.533 --> 00:08:48.120 (laughing) 220 00:08:48.120 --> 00:08:50.205 Let's follow up on a couple of things that you mentioned. 221 00:08:50.205 --> 00:08:53.440 One is, I think you and Shervin both talked 222 00:08:53.440 --> 00:08:56.030 about this briefly, but you know, there's a little bit 223 00:08:56.030 --> 00:08:58.570 of excitement about some of the bad things that happen. 224 00:08:58.570 --> 00:09:03.500 You know when we see these cases of AI bias coming out 225 00:09:03.500 --> 00:09:06.290 and they make headlines, you know, there's also 226 00:09:06.290 --> 00:09:08.800 a silver lining and that lining is pretty thick 227 00:09:08.800 --> 00:09:11.160 that it's really highlighting some of these things 228 00:09:11.160 --> 00:09:13.720 that are already existing or already going on 229 00:09:13.720 --> 00:09:15.597 and these seem like opportunities. 230 00:09:15.597 --> 00:09:17.940 But then at the same time, you also mentioned how 231 00:09:17.940 --> 00:09:20.232 when we react to those, we put things in place 232 00:09:20.232 --> 00:09:22.120 and more than a decade later, 233 00:09:22.120 --> 00:09:25.400 the DHS protections were still in place. 234 00:09:25.400 --> 00:09:28.234 So how do we balance between reacting to these things 235 00:09:28.234 --> 00:09:31.640 that come up between addressing biases 236 00:09:32.480 --> 00:09:35.280 and not putting in draconian measures 237 00:09:35.280 --> 00:09:37.470 that stifle innovation? 238 00:09:37.470 --> 00:09:39.770 You're right that there are opportunities. 239 00:09:39.770 --> 00:09:42.730 I think the idea is that depending 240 00:09:42.730 --> 00:09:45.330 on the challenge presented, I don't like the frame 241 00:09:45.330 --> 00:09:48.934 of stifling innovation or the tension between, you know, 242 00:09:48.934 --> 00:09:49.990 innovation and other values 243 00:09:49.990 --> 00:09:52.730 like security or privacy or safety. 244 00:09:52.730 --> 00:09:53.620 I think we're seeing this play 245 00:09:53.620 --> 00:09:54.960 out again in the pandemic, right? 246 00:09:54.960 --> 00:09:58.600 Where we are being often pushed a narrative 247 00:09:58.600 --> 00:10:01.570 around technologies that we need to deploy 248 00:10:01.570 --> 00:10:03.100 and technologies that we need to adopt 249 00:10:03.100 --> 00:10:05.330 in order to cope with the pandemic. 250 00:10:05.330 --> 00:10:06.960 And so we saw this in the debate 251 00:10:06.960 --> 00:10:09.670 over exposure notification and contact tracing apps. 252 00:10:09.670 --> 00:10:12.110 We're seeing this right now, very prominently 253 00:10:12.110 --> 00:10:13.310 in the conversation around things 254 00:10:13.310 --> 00:10:15.782 like immunity certificates and vaccine passports. 255 00:10:15.782 --> 00:10:17.756 I think the value of ethics there again, 256 00:10:17.756 --> 00:10:21.816 is that rather than look at the kind of narrow particulars 257 00:10:21.816 --> 00:10:24.390 and tweak around the edges of a specific technology 258 00:10:24.390 --> 00:10:27.680 or implementation, to step back and have that conversation 259 00:10:27.680 --> 00:10:30.380 about values and to have the conversation 260 00:10:30.380 --> 00:10:33.320 about what will we think of this in five or 10 years? 261 00:10:33.320 --> 00:10:35.220 So the silver lining of what happened 262 00:10:35.220 --> 00:10:37.820 after 9/11 was we've learned a lot of lessons about it. 263 00:10:37.820 --> 00:10:39.310 We've seen how, you know 264 00:10:39.310 --> 00:10:42.433 emergency infrastructure often becomes permanent. 265 00:10:42.433 --> 00:10:45.112 We've seen how those trade-offs in the moment 266 00:10:45.112 --> 00:10:47.840 might not be the right trade-offs in the long run. 267 00:10:47.840 --> 00:10:51.094 So I think if we don't take lessons from those, 268 00:10:51.094 --> 00:10:52.900 and this is where it's really interesting 269 00:10:52.900 --> 00:10:53.733 in technology ethics, 270 00:10:53.733 --> 00:10:56.350 how there's so much intersection with other things 271 00:10:56.350 --> 00:10:58.760 like STS and other fields around history 272 00:10:58.760 --> 00:11:00.790 and anthropology and why it's so critical 273 00:11:00.790 --> 00:11:02.642 to have this really interdisciplinary perspective. 274 00:11:02.642 --> 00:11:05.360 Because all of those things, 275 00:11:05.360 --> 00:11:08.007 again go back to a conversation about values and trade-offs 276 00:11:08.007 --> 00:11:10.100 and the prioritization of all of those. 277 00:11:10.100 --> 00:11:11.300 And some of that also of course 278 00:11:11.300 --> 00:11:12.970 has to do with time horizon, 279 00:11:12.970 --> 00:11:14.440 going back to your question before. 280 00:11:14.440 --> 00:11:16.530 So it's easy to take the short view, 281 00:11:16.530 --> 00:11:18.032 it can be hard to take the long view. 282 00:11:18.032 --> 00:11:20.239 I think if you have sort of an ethical lens 283 00:11:20.239 --> 00:11:22.213 it's important to balance both. 284 00:11:22.213 --> 00:11:24.320 Yeah, and also I think you're raising 285 00:11:24.320 --> 00:11:29.180 an interesting point that is with AI particularly, 286 00:11:29.180 --> 00:11:34.180 the consequences of a misstep is very longterm 287 00:11:36.000 --> 00:11:38.590 because the algorithms keep getting embedded 288 00:11:38.590 --> 00:11:40.010 and they multiply 289 00:11:40.010 --> 00:11:44.900 and by the time you find out, it might not be as easy 290 00:11:44.900 --> 00:11:47.710 as you just replace it with a different one 291 00:11:47.710 --> 00:11:50.280 because it has a cascading effect. 292 00:11:50.280 --> 00:11:51.701 On the point about innovation, 293 00:11:51.701 --> 00:11:56.392 AI can play a role in helping us be more ethical. 294 00:11:56.392 --> 00:11:58.071 We've seen examples, 295 00:11:58.071 --> 00:12:01.930 I think one of our guests talked about MasterCard, right? 296 00:12:01.930 --> 00:12:05.838 How they're using AI to understand the unconscious 297 00:12:05.838 --> 00:12:10.337 or unintended biases that their employees might have. 298 00:12:10.337 --> 00:12:13.900 What is your views on that, on AI specifically 299 00:12:13.900 --> 00:12:17.520 as a tool to really give us a better lens 300 00:12:17.520 --> 00:12:20.400 into biases that might exist? 301 00:12:20.400 --> 00:12:22.258 I think the challenge with AI is 302 00:12:22.258 --> 00:12:25.560 that it's so broad and definitions of AI 303 00:12:25.560 --> 00:12:27.810 really abound and there's not entire consensus 304 00:12:27.810 --> 00:12:29.518 around what we're even talking about. 305 00:12:29.518 --> 00:12:31.620 And so I think there's the risk that we sort of 306 00:12:31.620 --> 00:12:34.160 use this broad brush to characterize things 307 00:12:34.160 --> 00:12:36.640 that may or may not be beneficial. 308 00:12:36.640 --> 00:12:39.330 And then we run the risk of decontextualizing. 309 00:12:39.330 --> 00:12:41.820 So we can say, you know, we have a better outcome 310 00:12:41.820 --> 00:12:42.940 but relative to what? 311 00:12:42.940 --> 00:12:45.220 Or what were the trade-offs involved? 312 00:12:45.220 --> 00:12:47.240 And I think it's not just AI 313 00:12:47.240 --> 00:12:49.520 but it's the combination of a lot of new 314 00:12:49.520 --> 00:12:52.430 and advanced technologies that together are more 315 00:12:52.430 --> 00:12:53.810 than the sum of their parts, right? 316 00:12:53.810 --> 00:12:55.870 So AI plus network technologies, 317 00:12:55.870 --> 00:12:58.390 plus some of the ones I've mentioned earlier, 318 00:12:58.390 --> 00:13:02.050 I think are that much harder to sort of unwind 319 00:13:02.050 --> 00:13:04.290 or course correct, or, you know, 320 00:13:04.290 --> 00:13:06.070 remedy when things go wrong. 321 00:13:06.070 --> 00:13:08.422 So one of the challenges I see in the space 322 00:13:08.422 --> 00:13:11.020 is that again we can tweak around the edges 323 00:13:11.020 --> 00:13:13.470 and we'll look at a specific implementation 324 00:13:13.470 --> 00:13:14.990 or a specific tech stack 325 00:13:14.990 --> 00:13:17.360 and we won't look at it in the broader context. 326 00:13:17.360 --> 00:13:19.029 It's how does that fit into a system 327 00:13:19.029 --> 00:13:20.940 and what are the feedback loops 328 00:13:20.940 --> 00:13:24.260 and what are the implications for the system as a whole? 329 00:13:24.260 --> 00:13:26.029 And I think that's one of the areas where 330 00:13:26.029 --> 00:13:28.980 the technology ethics conversation is really useful 331 00:13:28.980 --> 00:13:32.400 particularly when you look at things like relational ethics 332 00:13:32.400 --> 00:13:34.450 and things that are a lot more concerned 333 00:13:34.450 --> 00:13:36.104 with systems and relationships 334 00:13:36.104 --> 00:13:39.470 and the interdependencies between them. 335 00:13:39.470 --> 00:13:40.830 I worry that we're a little too soon 336 00:13:40.830 --> 00:13:42.640 to declare victory there 337 00:13:42.640 --> 00:13:45.470 but definitely something to keep an eye on. 338 00:13:45.470 --> 00:13:46.430 Yeah I mean as you say, 339 00:13:46.430 --> 00:13:47.890 the devil's in the detail. 340 00:13:47.890 --> 00:13:49.460 This is the beginning of having a dialogue 341 00:13:49.460 --> 00:13:51.892 and having a conversation on a topic that otherwise, 342 00:13:51.892 --> 00:13:54.380 you know, would not even be on the radar 343 00:13:54.380 --> 00:13:56.283 of many, many people. 344 00:13:56.283 --> 00:14:00.280 What is your advice to executives and technologists 345 00:14:00.280 --> 00:14:04.270 that are right now building technology and algorithms? 346 00:14:04.270 --> 00:14:08.910 Like what do they do in this early stages 347 00:14:08.910 --> 00:14:11.690 of having this dialogue? 348 00:14:11.690 --> 00:14:13.711 Yeah, that's a tough question. 349 00:14:13.711 --> 00:14:16.270 Of course it depends on their role. 350 00:14:16.270 --> 00:14:17.870 So you can see how the incentives are very different 351 00:14:17.870 --> 00:14:20.010 for employees versus, you know, 352 00:14:20.010 --> 00:14:23.330 executives, versus shareholders, or board members. 353 00:14:23.330 --> 00:14:25.380 So thinking about those incentives is important 354 00:14:25.380 --> 00:14:28.010 in terms of framing the way to approach this, 355 00:14:28.010 --> 00:14:30.652 that being said, there are a lot of resources now 356 00:14:30.652 --> 00:14:32.959 and there's a lot available in terms of self-education. 357 00:14:32.959 --> 00:14:35.380 And so I don't really think there's an excuse 358 00:14:35.380 --> 00:14:38.000 at this point to not really understand 359 00:14:38.000 --> 00:14:41.070 the pillars of the conversation, the core texts, 360 00:14:41.070 --> 00:14:42.658 the core materials, the core videos, 361 00:14:42.658 --> 00:14:45.080 some of the principles that we talked about before. 362 00:14:45.080 --> 00:14:47.997 I think there's so much available by way of research 363 00:14:47.997 --> 00:14:50.742 and tools and materials to understand 364 00:14:50.742 --> 00:14:54.790 what's at stake, that to not think about one's work 365 00:14:54.790 --> 00:14:58.010 in that context feels more than negligent at this point. 366 00:14:58.010 --> 00:14:59.178 It almost feels reckless in some ways. 367 00:14:59.178 --> 00:15:02.715 Nevertheless, I think the importance is to 368 00:15:02.715 --> 00:15:05.534 contextualize your work, to take a step back. 369 00:15:05.534 --> 00:15:07.265 This is really hard for corporations, 370 00:15:07.265 --> 00:15:09.155 especially ones with shareholders. 371 00:15:09.155 --> 00:15:13.270 So we can understand that, we can hold both as true 372 00:15:13.270 --> 00:15:17.415 at the same time, and think about taking it upon yourself. 373 00:15:17.415 --> 00:15:20.710 You know, there are more formal means of education 374 00:15:20.710 --> 00:15:23.310 so one of the things that we are doing, the lab of course 375 00:15:23.310 --> 00:15:26.570 is trying to develop a very tangible curriculum 376 00:15:26.570 --> 00:15:28.981 for exactly the stakeholders that you mentioned, 377 00:15:28.981 --> 00:15:31.200 and with the specific idea 378 00:15:31.200 --> 00:15:32.960 to take some of the core scholarship 379 00:15:32.960 --> 00:15:34.880 and translate it into practice, 380 00:15:34.880 --> 00:15:36.590 that would become a useful tool as well. 381 00:15:36.590 --> 00:15:38.220 But at the end of the day, I think it's a matter 382 00:15:38.220 --> 00:15:41.620 of perspective and accepting responsibility for the fact 383 00:15:41.620 --> 00:15:43.740 that no one person can solve this, 384 00:15:43.740 --> 00:15:45.520 at the same time, we can't solve this 385 00:15:45.520 --> 00:15:49.710 unless everyone sort of acknowledges that they play a part. 386 00:15:49.710 --> 00:15:51.730 And that ties into the things your lab 387 00:15:51.730 --> 00:15:52.673 is doing because you know, 388 00:15:52.673 --> 00:15:55.670 I think the idea of everybody learning a lot 389 00:15:55.670 --> 00:15:58.390 about ethics kind of makes sense at one level, 390 00:15:58.390 --> 00:16:00.830 on the other hand, we also know we've seen with privacy 391 00:16:00.830 --> 00:16:04.590 that people are lazy and we are all somewhat lazy, 392 00:16:04.590 --> 00:16:06.550 we'll trade short term for long term. 393 00:16:06.550 --> 00:16:10.060 And it seems like some of what your lab is trying to set up 394 00:16:10.060 --> 00:16:11.595 is making that infrastructure available 395 00:16:11.595 --> 00:16:14.745 to reduce the cost, to make it easier for practitioners 396 00:16:14.745 --> 00:16:17.787 to get access to those sorts of tools. 397 00:16:17.787 --> 00:16:19.320 Yeah and I think education 398 00:16:19.320 --> 00:16:21.080 is not a substitute for regulation. 399 00:16:21.080 --> 00:16:23.090 So I think ultimately 400 00:16:23.090 --> 00:16:25.740 it's not on individuals, it's not on consumers. 401 00:16:25.740 --> 00:16:27.060 My remarks should be taken 402 00:16:27.060 --> 00:16:29.630 as saying that the responsibility to really, you know 403 00:16:29.630 --> 00:16:33.250 reduce the mitigate harms is on individuals entirely. 404 00:16:33.250 --> 00:16:36.240 I think the point is that we just have to be careful 405 00:16:36.240 --> 00:16:37.880 that we don't wait for regulation. 406 00:16:37.880 --> 00:16:39.630 One of the things that I particularly like 407 00:16:39.630 --> 00:16:41.550 about the technology ethics space 408 00:16:41.550 --> 00:16:44.320 is that it takes away the excuse to not think 409 00:16:44.320 --> 00:16:47.050 about these things before we're forced to, right? 410 00:16:47.050 --> 00:16:48.630 So I think in the past 411 00:16:48.630 --> 00:16:50.250 there's sort of been this luxury in tech 412 00:16:50.250 --> 00:16:53.340 of waiting to be forced into taking decisions 413 00:16:53.340 --> 00:16:56.742 or making trade-offs, or confronting issues. 414 00:16:56.742 --> 00:16:59.298 Now, I would say with tech ethics, 415 00:16:59.298 --> 00:17:01.270 you can't really do that anymore. 416 00:17:01.270 --> 00:17:02.640 I think the zeitgeist has changed, 417 00:17:02.640 --> 00:17:03.950 the market has changed. 418 00:17:03.950 --> 00:17:06.962 Things are so far from perfect, things are far from good 419 00:17:06.962 --> 00:17:09.610 but at least in that regard, 420 00:17:09.610 --> 00:17:10.800 you can't hide from this. 421 00:17:10.800 --> 00:17:12.687 I think in that way 422 00:17:12.687 --> 00:17:14.660 they're at least somewhat better than they were. 423 00:17:14.660 --> 00:17:15.493 I also feel like 424 00:17:15.493 --> 00:17:19.263 part of that is many organizations, to Elizabeth's point, 425 00:17:19.263 --> 00:17:22.010 not only they don't have the dialogue, 426 00:17:22.010 --> 00:17:24.000 even if they did, they don't have 427 00:17:24.000 --> 00:17:28.182 the necessary infrastructure, or investments, 428 00:17:28.182 --> 00:17:31.300 or incentives to actually have those conversations. 429 00:17:31.300 --> 00:17:34.490 And so I think I go back to your earlier point, Elizabeth, 430 00:17:34.490 --> 00:17:36.840 that is like, you know, we have to have the right incentives 431 00:17:36.840 --> 00:17:39.150 and organizations have to have with or without 432 00:17:39.150 --> 00:17:42.255 the regulation have the investment and the incentives 433 00:17:42.255 --> 00:17:46.440 to actually put in place the tools and resources 434 00:17:46.440 --> 00:17:49.890 to have these conversations and make an impact. 435 00:17:49.890 --> 00:17:51.440 You have to also align the incentives. 436 00:17:51.440 --> 00:17:52.330 Some of these companies, 437 00:17:52.330 --> 00:17:54.417 I think actually want to do the right thing, 438 00:17:54.417 --> 00:17:56.853 but again, they're sort of beholden to quarterly reports 439 00:17:56.853 --> 00:17:59.490 and shareholders and resolutions 440 00:17:59.490 --> 00:18:01.210 and they need the incentives, 441 00:18:01.210 --> 00:18:03.630 they need the backing from the outside to be able to 442 00:18:03.630 --> 00:18:05.170 do what it is that is probably 443 00:18:05.170 --> 00:18:07.100 in their longer-term interest. 444 00:18:07.100 --> 00:18:08.874 You mentioned incentives a few times. 445 00:18:08.874 --> 00:18:11.970 Can we get some specifics for things that we could do 446 00:18:11.970 --> 00:18:15.330 around that to help align those incentives better? 447 00:18:15.330 --> 00:18:16.550 What would do it? 448 00:18:16.550 --> 00:18:18.570 I think the sort of process oriented 449 00:18:18.570 --> 00:18:19.920 regulations make sense, right? 450 00:18:19.920 --> 00:18:22.410 So what incentive does the company have right now 451 00:18:22.410 --> 00:18:23.800 to audit its algorithms 452 00:18:23.800 --> 00:18:25.973 and then be transparent about the results? 453 00:18:25.973 --> 00:18:28.370 None, they might actually want to know that, 454 00:18:28.370 --> 00:18:30.620 they might actually want an independent third-party audit 455 00:18:30.620 --> 00:18:33.250 that might actually be helpful from a risk standpoint. 456 00:18:33.250 --> 00:18:36.210 If you have a law that says you have to do it, 457 00:18:36.210 --> 00:18:38.010 most companies will probably do it. 458 00:18:38.010 --> 00:18:40.182 So I think those types of, you know, 459 00:18:40.182 --> 00:18:41.540 they're not even nudges. 460 00:18:41.540 --> 00:18:44.540 I mean they're clear interventions, are really useful. 461 00:18:44.540 --> 00:18:46.540 I think the same is true of 462 00:18:46.540 --> 00:18:48.932 things like board expertise and composition. 463 00:18:48.932 --> 00:18:50.415 And we may want to think about 464 00:18:50.415 --> 00:18:53.600 is it useful to have super class share structures 465 00:18:53.600 --> 00:18:57.240 in Silicon Valley where basically no one has 466 00:18:57.240 --> 00:18:59.153 any control over the company's destiny apart from, 467 00:18:59.153 --> 00:19:01.267 you know, one or two people. 468 00:19:01.267 --> 00:19:03.530 So I think these are all again, 469 00:19:03.530 --> 00:19:06.391 common interventions in other sectors and other industries. 470 00:19:06.391 --> 00:19:08.690 And the problem is that this sort of 471 00:19:08.690 --> 00:19:11.900 technology exceptionalism was problematic before, 472 00:19:11.900 --> 00:19:13.972 but now when every company is a tech company, 473 00:19:13.972 --> 00:19:15.775 the problem is just metastasized 474 00:19:15.775 --> 00:19:18.880 to a completely different scale. 475 00:19:18.880 --> 00:19:20.620 The analogy I think about is food. 476 00:19:20.620 --> 00:19:23.430 I mean, anything that sells food now we want them 477 00:19:23.430 --> 00:19:25.120 to follow food regulations. 478 00:19:25.120 --> 00:19:27.050 That certainly wasn't the case a hundred years ago 479 00:19:27.050 --> 00:19:29.690 when Upton Sinclair had the jungle. 480 00:19:29.690 --> 00:19:31.560 I mean, it took that to bring that sort 481 00:19:31.560 --> 00:19:34.307 of transparency and scrutiny to food related processes 482 00:19:34.307 --> 00:19:37.660 but we don't make exceptions now for, oh well 483 00:19:37.660 --> 00:19:40.200 you know, you're just feeding a hundred people. 484 00:19:40.200 --> 00:19:42.233 We're not going to force you 485 00:19:42.233 --> 00:19:43.758 to comply with health regulations. 486 00:19:43.758 --> 00:19:45.130 Exactly. 487 00:19:45.130 --> 00:19:47.482 Yeah, I think that's actually 488 00:19:47.482 --> 00:19:48.315 a very good analogy Sam, 489 00:19:48.315 --> 00:19:51.004 because as I was thinking about what Elizabeth was saying, 490 00:19:51.004 --> 00:19:55.180 my mind went into just also ignorance. 491 00:19:55.180 --> 00:19:57.470 I mean, I think many users 492 00:19:57.470 --> 00:20:00.575 of a lot of these technologies, highly, highly 493 00:20:00.575 --> 00:20:02.590 you know, senior people, highly, 494 00:20:02.590 --> 00:20:05.527 highly educated people may not even be aware 495 00:20:05.527 --> 00:20:10.527 of what the outputs are or what the interim outputs are 496 00:20:10.990 --> 00:20:13.525 or how they come about, or like what all 497 00:20:13.525 --> 00:20:17.700 of the hundreds and thousands of features that give rise 498 00:20:17.700 --> 00:20:20.660 to what the algorithm is doing is actually doing. 499 00:20:20.660 --> 00:20:23.530 And so it's a little bit like the ingredients 500 00:20:23.530 --> 00:20:25.310 in food where we had no idea 501 00:20:25.310 --> 00:20:28.193 some things are bad for us and some things would kill us 502 00:20:28.193 --> 00:20:30.670 and some things that we thought were better for us 503 00:20:30.670 --> 00:20:33.310 than the other bad thing are actually worse for us. 504 00:20:33.310 --> 00:20:37.140 So I think all of that, it's bringing some light 505 00:20:37.140 --> 00:20:41.805 into that education as well as regulation and incentives. 506 00:20:41.805 --> 00:20:43.490 The point is we acted 507 00:20:43.490 --> 00:20:45.760 before we had perfect information and knowledge. 508 00:20:45.760 --> 00:20:47.895 And I think there's a tendency in this space to say, 509 00:20:47.895 --> 00:20:49.170 we can't do anything, 510 00:20:49.170 --> 00:20:52.147 we can't intervene until we had to know exactly 511 00:20:52.147 --> 00:20:53.290 what this tech is, 512 00:20:53.290 --> 00:20:54.930 what the innovation looks like. 513 00:20:54.930 --> 00:20:56.330 You know, we got food wrong, right? 514 00:20:56.330 --> 00:20:58.185 We had the wrong dietary guidelines. 515 00:20:58.185 --> 00:20:59.610 We readjusted them. 516 00:20:59.610 --> 00:21:01.020 We came back to the drawing board 517 00:21:01.020 --> 00:21:03.380 and we recalibrated, the American diet looks different 518 00:21:03.380 --> 00:21:05.208 I mean it's still atrocious but can rethink it. 519 00:21:05.208 --> 00:21:08.573 But we keep revisiting it, which is your point. 520 00:21:08.573 --> 00:21:09.840 We keep revisiting and we reiterate. 521 00:21:09.840 --> 00:21:11.300 And so that's exactly what we need to do 522 00:21:11.300 --> 00:21:13.300 in this space and say, based on what we know now 523 00:21:13.300 --> 00:21:14.310 and that's science, right? 524 00:21:14.310 --> 00:21:16.553 Fundamentally science is sort of the consensus we have 525 00:21:16.553 --> 00:21:17.740 at a given time. 526 00:21:17.740 --> 00:21:18.800 It doesn't mean it's perfect. 527 00:21:18.800 --> 00:21:20.870 It doesn't mean it won't change, but it means 528 00:21:20.870 --> 00:21:22.377 that we don't get paralyzed, but we act 529 00:21:22.377 --> 00:21:25.110 with the best knowledge that we have and the humility 530 00:21:25.110 --> 00:21:28.080 that we'll probably have to change this or look at it again. 531 00:21:28.080 --> 00:21:30.510 So, you know, the same thing happened with the pandemic 532 00:21:30.510 --> 00:21:33.940 where we have the WHO saying that masks weren't effective 533 00:21:33.940 --> 00:21:35.320 and then changing course. 534 00:21:35.320 --> 00:21:38.950 But we respect that process because there's the humility 535 00:21:38.950 --> 00:21:40.740 and the transparency to say 536 00:21:40.740 --> 00:21:42.905 that this is how we're going to operate collectively 537 00:21:42.905 --> 00:21:46.900 because we can't afford to just do nothing. 538 00:21:46.900 --> 00:21:49.090 And I think that's where we are right now. 539 00:21:49.090 --> 00:21:49.923 Very well said. 540 00:21:49.923 --> 00:21:50.800 Well, 541 00:21:50.800 --> 00:21:53.170 I really like how you illustrate all these benefits 542 00:21:53.170 --> 00:21:56.880 and how you make that a concrete thing for people. 543 00:21:56.880 --> 00:21:59.250 And I hope that the lab takes off and does well 544 00:21:59.250 --> 00:22:01.190 and makes some progress and provides some infrastructure 545 00:22:01.190 --> 00:22:02.950 for people to make it easier for that. 546 00:22:02.950 --> 00:22:04.800 Thank you for taking the time to talk with us today. 547 00:22:04.800 --> 00:22:06.120 Yeah, thank you so much. 548 00:22:06.120 --> 00:22:07.190 Thanks so much for having me. 549 00:22:07.190 --> 00:22:08.788 This was great. 550 00:22:08.788 --> 00:22:11.205 (calm music) 551 00:22:14.337 --> 00:22:15.720 Shervin, Elizabeth had a lot of good points 552 00:22:15.720 --> 00:22:17.841 about getting started now. 553 00:22:17.841 --> 00:22:18.710 What struck you as interesting 554 00:22:18.710 --> 00:22:22.610 or what struck you as a way that companies could start now? 555 00:22:22.610 --> 00:22:25.210 I think the most striking thing she said, 556 00:22:25.210 --> 00:22:27.570 I mean she said a lot of very, very insightful things 557 00:22:27.570 --> 00:22:31.820 but in terms of how to get going, she made it very simple. 558 00:22:31.820 --> 00:22:33.559 She said, look, this is ultimately about values. 559 00:22:33.559 --> 00:22:35.811 And if it's something you care about 560 00:22:35.811 --> 00:22:38.788 and we know many, many organizations and many, 561 00:22:38.788 --> 00:22:42.330 many people and many very senior people 562 00:22:42.330 --> 00:22:44.340 and powerful people do care about it. 563 00:22:44.340 --> 00:22:46.580 If you care about it, then do something about it. 564 00:22:46.580 --> 00:22:48.360 But the striking thing she said is 565 00:22:48.360 --> 00:22:50.390 that you have to have the right people 566 00:22:50.390 --> 00:22:53.216 at the table and you have to start having the conversations. 567 00:22:53.216 --> 00:22:56.400 And as you said, Sam, this is a business problem. 568 00:22:56.400 --> 00:22:57.760 That's a very managerial thing. 569 00:22:57.760 --> 00:22:59.040 Yeah, it's a managerial thing, 570 00:22:59.040 --> 00:23:02.590 it's about allocation of resources to solve a problem. 571 00:23:02.590 --> 00:23:04.693 And it is a fact that some organizations do allocate 572 00:23:04.693 --> 00:23:08.738 resources on responsible AI and governance, 573 00:23:08.738 --> 00:23:13.380 AI governance and ethical AI, and some organizations don't. 574 00:23:13.380 --> 00:23:15.960 And so I think that's the key lesson from here 575 00:23:15.960 --> 00:23:17.310 is that if you care about it 576 00:23:17.310 --> 00:23:19.320 you don't have to wait for all the regulation 577 00:23:19.320 --> 00:23:20.620 to settle down. 578 00:23:20.620 --> 00:23:22.780 I liked her point about revisiting it as well. 579 00:23:22.780 --> 00:23:26.120 And that comes with the idea of not starting perfectly 580 00:23:26.120 --> 00:23:28.198 just plan to come back to it, plan to revisit it 581 00:23:28.198 --> 00:23:31.620 because these things, even as you said, Shervin 582 00:23:31.620 --> 00:23:34.580 if you got it perfect, technology would change on us. 583 00:23:34.580 --> 00:23:36.010 Exactly and you would never know 584 00:23:36.010 --> 00:23:37.462 you got it perfect. 585 00:23:37.462 --> 00:23:38.295 You never know you got it perfect. 586 00:23:38.295 --> 00:23:41.380 Yeah, the perfection would be lost in immortality, so. 587 00:23:41.380 --> 00:23:42.900 I'm still trying to figure out if coffee 588 00:23:42.900 --> 00:23:45.260 is good for your heart or bad for your heart 589 00:23:45.260 --> 00:23:48.900 because it's gone from good to bad many times. 590 00:23:48.900 --> 00:23:50.460 Well, I mean, and I think that's, you know, 591 00:23:50.460 --> 00:23:52.350 some of what people face with a complex problem. 592 00:23:52.350 --> 00:23:54.480 I mean, if this was an easy problem, 593 00:23:54.480 --> 00:23:56.061 we wouldn't be having this conversation. 594 00:23:56.061 --> 00:23:58.350 If there were simple solutions, you know, 595 00:23:58.350 --> 00:24:00.540 if people are tuning in to say, alright, 596 00:24:00.540 --> 00:24:02.256 here are the four things that I need to do to solve 597 00:24:02.256 --> 00:24:04.828 ethical problems with artificial intelligence, 598 00:24:04.828 --> 00:24:08.130 we're not going to be able to offer that. 599 00:24:08.130 --> 00:24:09.650 We're not quite that Buzzfeed level 600 00:24:09.650 --> 00:24:12.600 of being able to say, here's what we can do 601 00:24:12.600 --> 00:24:13.456 because it's hard. 602 00:24:13.456 --> 00:24:15.400 The other thing that struck me is that, 603 00:24:15.400 --> 00:24:18.566 you know she has a lot of education and passion 604 00:24:18.566 --> 00:24:20.876 in this space that I think is actually quite contagious 605 00:24:20.876 --> 00:24:24.100 because I think that's exactly the mentality 606 00:24:24.100 --> 00:24:26.406 and the attitude that many organizations 607 00:24:26.406 --> 00:24:30.390 can start to be inspired by and adopt 608 00:24:30.390 --> 00:24:32.528 to start moving in the right direction 609 00:24:32.528 --> 00:24:34.820 rather than waiting for government 610 00:24:34.820 --> 00:24:37.030 or regulation to solve this problem. 611 00:24:37.030 --> 00:24:41.507 We can all take a role in becoming more responsible 612 00:24:41.507 --> 00:24:45.650 and more ethical with AI starting now. 613 00:24:45.650 --> 00:24:48.240 We already have the right values 614 00:24:48.240 --> 00:24:50.300 and we already know what's important. 615 00:24:50.300 --> 00:24:51.760 Nothing is really stopping us 616 00:24:51.760 --> 00:24:54.700 from having those dialogues and making those changes. 617 00:24:54.700 --> 00:24:56.030 (calm music) 618 00:24:56.030 --> 00:24:57.630 Thanks for listening to season two 619 00:24:57.630 --> 00:24:59.440 of Me, Myself, and AI. 620 00:24:59.440 --> 00:25:00.410 We'll be back in the Fall 621 00:25:00.410 --> 00:25:02.420 with new episodes for season three. 622 00:25:02.420 --> 00:25:03.340 And in the meantime, 623 00:25:03.340 --> 00:25:06.140 we're dropping a bonus episode on July 13th. 624 00:25:06.140 --> 00:25:08.250 Join us as we interview Dave Johnson, 625 00:25:08.250 --> 00:25:10.410 Chief Data and Artificial Intelligence Officer 626 00:25:10.410 --> 00:25:12.269 at Moderna, about how the company used AI 627 00:25:12.269 --> 00:25:16.034 to accelerate its development of the COVID-19 vaccine. 628 00:25:16.034 --> 00:25:19.130 In the meantime, to continue the conversation with us, 629 00:25:19.130 --> 00:25:21.440 you can find us in a special LinkedIn group created 630 00:25:21.440 --> 00:25:23.100 for listeners just like you. 631 00:25:23.100 --> 00:25:25.270 It's called AI for Leaders. 632 00:25:25.270 --> 00:25:27.170 We'll put a link to it in the show notes 633 00:25:27.170 --> 00:25:30.610 or you can visit MITSMR.com/aiforleaders 634 00:25:30.610 --> 00:25:33.830 to be redirected to the LinkedIn page. 635 00:25:33.830 --> 00:25:35.910 Request to join and as soon as you do, 636 00:25:35.910 --> 00:25:37.890 you'll be able to catch up on back episodes 637 00:25:37.890 --> 00:25:39.490 of Me, Myself, and AI, 638 00:25:39.490 --> 00:25:41.198 talk with the show creators and hosts, 639 00:25:41.198 --> 00:25:42.930 meet some of the guests, 640 00:25:42.930 --> 00:25:45.380 and share other resources that help business leaders 641 00:25:45.380 --> 00:25:47.200 stay on top of all things AI. 642 00:25:47.200 --> 00:25:48.371 Talk to you soon. 643 00:25:48.371 --> 00:25:50.788 (calm music)