Sharing AI Mistakes: Partnership on AI’s Rebecca Finlay

**Shervin Khodabandeh** (0:00)
Stay tuned after today's episode to hear Sam and I break down the key points made by our guest.

**Sam Ransbotham** (0:08)
We can all certainly learn from company successes with AI, but what about from their failures? On today's episode, we speak with one leader who encourages organizations to share the bad along with the good in hopes that we can all learn together.

**Rebecca Finlay** (0:24)
I'm Rebecca Finlay from Partnership on AI, and you're listening to Me, Myself, and AI.

**Sam Ransbotham** (0:30)
Welcome to Me, Myself, and AI, a podcast on artificial intelligence and business. Each episode, we introduce you to someone innovating with AI. I'm Sam Ransbotham, Professor of Analytics at Boston College. I'm also the AI and Business Strategy guest editor at MIT Sloan Management Review.

**Shervin Khodabandeh** (0:49)
I'm Shervin Khodabandeh, senior partner with BCG and one of the leaders of our AI business. Together, MIT Smr and BCG have been researching and publishing on AI since 2017 Interviewing hundreds of practitioners and surveying thousands of companies on what it takes to build and to deploy and scale AI capabilities, and really transform the way organizations operate.
Hi, everyone. Thanks for joining us today. Sam and I are very happy to be speaking with Rebecca Finlay, CEO of Partnership on AI. The organization is a non-profit that brings together a community of more than 100 partners to create tools, recommendations, and other resources to ensure we're all building and deploying AI solutions ethically. Rebecca, this is super exciting and important work, and we'd love to be speaking to you about it. Thanks for joining the show.

**Rebecca Finlay** (1:42)
Thank you so much for having me. I've been looking forward to this conversation.

**Shervin Khodabandeh** (1:46)
Wonderful. So let's get started. Tell us more about the organization's mission and purpose.

**Rebecca Finlay** (1:52)
The Partnership on AI was formed in 2016 with the belief that we needed to bring diverse perspectives together in order to address the ethical and responsible challenges that come with the development of artificial intelligence, and also to realize the opportunities to truly ensure that the innovation of AI benefits people and communities. And so with that belief in mind, a group of companies and civil society advocates and researchers came together to chart out a mission to build a global community that has now come together for many years focused on ensuring that we're developing AI that works for people, that works for workers, that drives innovation, that is sustainable and responsible privacy protecting and really enhancing equity and justice and shared prosperity.

**Shervin Khodabandeh** (2:52)
Maybe give us an example or some examples of the companies and the type of research.

**Rebecca Finlay** (2:58)
The very first investment that was made into the Partnership on AI was by the six large technology companies. So that's Amazon and Apple, Microsoft, Facebook, now Meta, Google, DeepMind and IBM. It was really at that moment when this new version of AI or what was new then, deep learning, pre-generative AI, that wave of AI was really starting to be deployed in internet search mechanisms, in mapping mechanisms, in recommendation engines, and the realization that there were some important ethical questions that needed to be answered.
That brought together a whole group of other private sector companies, but also organizations like the ACLU and research institutes at Berkeley, and Stanford, and Harvard, and internationally as well. So organizations like the Alan Turing Institute in the UK and beyond. And so that group came together, and now we have a number of different working groups that are really focusing both on the impact of that predictive AI, but even more importantly, the potential impact of generative AI foundation and frontier models.

**Sam Ransbotham** (4:17)
What are some examples of some progress that you feel like the partnership has made? What are some specifics here?

**Rebecca Finlay** (4:23)
Particularly in this area, it's clear that we need to think about it through what we would call a socio-technical lens. Yes, there are technical standards like watermarking or standards like C2PA that are thinking about how you clearly track the authenticity of a piece of media through the cycle, but you also need to think about what are the social systems and structures in place. So one of the efforts that we developed and now have 18 organizations signed up and evolving with us is the framework for responsible development of synthetic media, and that is really looking across the value chain. What are the responsibilities of creators, developers, deployers, that's platforms and otherwise. When it comes to thinking about how to disclose appropriately to make sure that whoever comes in contact with the media that is developed is aware that it is AI generated in some way, and also to make sure that the media that is being developed is not being maliciously used or being used in any way to harm. And we have a whole series of lists and information about what those harms are and why we need to be protecting people from them. So that's a really important effort. And of course, the question is, how is it being used? And so one piece of this work that we've been doing is to ensure that the companies and organizations and media agencies that have signed up to support this work are really being transparent about how they are using this to respond to real world circumstances. And so we make that available. And the goal is, yes, both to be accountable in terms of the framework itself, but also to try to create case studies that other organizations can use and learn from as well.