Women in AI: Claire Leibowicz, AI and media integrity expert at PAI

16 Min Read

To present AI-focused girls lecturers and others their well-deserved — and overdue — time within the highlight, TechCrunch is launching a collection of interviews specializing in exceptional girls who’ve contributed to the AI revolution. We’ll publish a number of items all year long because the AI growth continues, highlighting key work that always goes unrecognized. Learn extra profiles right here.

Claire Leibowicz is the top of the AI and media integrity program on the Partnership on AI (PAI), the trade group backed by Amazon, Meta, Google, Microsoft and others dedicated to the “accountable” deployment of AI tech. She additionally oversees PAI’s AI and media integrity steering committee.

In 2021, Leibowicz was a journalism fellow at Pill Journal, and in 2022, she was a fellow at The Rockefeller Basis’s Bellagio Middle targeted on AI governance. Leibowicz — who holds a BA in psychology and pc science from Harvard and a grasp’s diploma from Oxford — has suggested corporations, governments and nonprofit organizations on AI governance, generative media and digital data.


Briefly, how did you get your begin in AI? What attracted you to the sphere?

It could appear paradoxical, however I got here to the AI subject from an curiosity in human conduct. I grew up in New York, and I used to be all the time captivated by the various methods folks there work together and the way such a various society takes form. I used to be inquisitive about large questions that have an effect on fact and justice, like how will we select to belief others? What prompts intergroup battle? Why do folks consider sure issues to be true and never others? I began out exploring these questions in my tutorial life via cognitive science analysis, and I shortly realized that expertise was affecting the solutions to those questions. I additionally discovered it intriguing how synthetic intelligence might be a metaphor for human intelligence.

That introduced me into pc science school rooms the place school — I’ve to shout out Professor Barbara Grosz, who’s a trailblazer in pure language processing, and Professor Jim Waldo, who blended his philosophy and pc science background — underscored the significance of filling their school rooms with non-computer science and -engineering majors to give attention to the social influence of applied sciences, together with AI. And this was earlier than “AI ethics” was a definite and in style subject. They made clear that, whereas technical understanding is helpful, expertise impacts huge realms together with geopolitics, economics, social engagement and extra, thereby requiring folks from many disciplinary backgrounds to weigh in on seemingly technological questions.

Whether or not you’re an educator excited about how generative AI instruments have an effect on pedagogy, a museum curator experimenting with a predictive route for an exhibit or a health care provider investigating new picture detection strategies for studying lab reviews, AI can influence your subject. This actuality, that AI touches many domains, intrigued me: there was mental selection inherent to working within the AI subject, and this introduced with it an opportunity to influence many aspects of society.

What work are you most happy with (within the AI subject)?

See also  Women In AI: Irene Solaiman, head of global policy at Hugging Face

I’m happy with the work in AI that brings disparate views collectively in a stunning and action-oriented approach — that not solely accommodates, however encourages, disagreement. I joined the PAI because the group’s second employees member six years in the past, and sensed straight away the group was trailblazing in its dedication to numerous views. PAI noticed such work as an important prerequisite to AI governance that mitigates hurt and results in sensible adoption and influence within the AI subject. This has confirmed true, and I’ve been heartened to assist form PAI’s embrace of multidisciplinarity and watch the establishment develop alongside the AI subject.

Our work on artificial media over the previous six years began nicely earlier than generative AI turned a part of the general public consciousness, and exemplifies the chances of multistakeholder AI governance. In 2020, we labored with 9 totally different organizations from civil society, trade and media to form Fb’s Deepfake Detection Problem, a machine studying competitors for constructing fashions to detect AI-generated media. These outdoors views helped form the equity and targets of the successful fashions — displaying how human rights specialists and journalists can contribute to a seemingly technical query like deepfake detection. Final yr, we revealed a normative set of steering on accountable artificial media — PAI’s Responsible Practices for Synthetic Media — that now has 18 supporters from extraordinarily totally different backgrounds, starting from OpenAI to TikTok to Code for Africa, Bumble, BBC and WITNESS. With the ability to put pen to paper on actionable steering that’s knowledgeable by technical and social realities is one factor, nevertheless it’s one other to truly get institutional assist. On this case, establishments dedicated to offering transparency reviews about how they navigate the artificial media subject. AI initiatives that characteristic tangible steering, and present the way to implement that steering throughout establishments, are a number of the most significant to me.

How do you navigate the challenges of the male-dominated tech trade, and, by extension, the male-dominated AI trade?

I’ve had each fantastic female and male mentors all through my profession. Discovering individuals who concurrently assist and problem me is vital to any development I’ve skilled. I discover that specializing in shared pursuits and discussing the questions that animate the sphere of AI can deliver folks with totally different backgrounds and views collectively. Apparently, PAI’s workforce is made up of greater than half girls, and lots of the organizations engaged on AI and society or accountable AI questions have many ladies on employees. That is usually in distinction to these engaged on engineering and AI analysis groups, and is a step in the appropriate path for illustration within the AI ecosystem.

What recommendation would you give to girls searching for to enter the AI subject?

As I touched on within the earlier query, a number of the primarily male-dominated areas inside AI that I’ve encountered have additionally been these which are essentially the most technical. Whereas we should always not prioritize technical acumen over different types of literacy within the AI subject, I’ve discovered that having technical coaching has been a boon to each my confidence, and effectiveness, in such areas. We’d like equal illustration in technical roles and an openness to the experience of oldsters who’re specialists in different fields like civil rights and politics which have extra balanced illustration. On the identical time, equipping extra girls with technical literacy is vital to balancing illustration within the AI subject.

See also  Apple researchers develop AI that can 'see' and understand screen context

I’ve additionally discovered it enormously significant to attach with girls within the AI subject who’ve navigated balancing household {and professional} life. Discovering function fashions to speak to about massive questions associated to profession and parenthood — and a number of the distinctive challenges girls nonetheless face at work — has made me really feel higher outfitted to deal with some these challenges as they come up.

What are a number of the most urgent points dealing with AI because it evolves?

The questions of fact and belief on-line — and offline — change into more and more difficult as AI evolves. As content material starting from photos to movies to textual content might be AI-generated or modified, is seeing nonetheless believing? How can we depend on proof if paperwork can simply and realistically be doctored? Can now we have human-only areas on-line if it’s extraordinarily simple to mimic an actual particular person? How will we navigate the tradeoffs that AI presents between free expression and the chance that AI methods may cause hurt? Extra broadly, how will we guarantee the knowledge atmosphere shouldn’t be solely formed by a choose few corporations and people working for them however incorporates the views of stakeholders from around the globe, together with the general public?

Alongside these particular questions, PAI has been concerned in different aspects of AI and society, together with how we take into account equity and bias in an period of algorithmic choice making, how labor impacts and is impacted by AI, the way to navigate accountable deployment of AI methods and even the way to make AI methods extra reflective of myriad views. At a structural degree, we should take into account how AI governance can navigate huge tradeoffs by incorporating different views.

What are some points AI customers ought to pay attention to?

First, AI customers ought to know that if one thing sounds too good to be true, it most likely is.

The generative AI growth over the previous yr has, in fact, mirrored huge ingenuity and innovation, nevertheless it has additionally led to public messaging round AI that’s usually hyperbolic and inaccurate.

AI customers must also perceive that AI shouldn’t be revolutionary, however exacerbating and augmenting current issues and alternatives. This doesn’t imply they need to take AI much less severely, however relatively use this information as a useful basis for navigating an more and more AI-infused world. For instance, if you’re involved about the truth that folks may mis-contextualize a video earlier than an election by altering the caption, try to be involved in regards to the velocity and scale at which they will mislead utilizing deepfake expertise. In case you are involved about using surveillance within the office, you must also take into account how AI will make such surveillance simpler and extra pervasive. Sustaining a wholesome skepticism in regards to the novelty of AI issues, whereas additionally being sincere about what’s distinct in regards to the present second, is a useful body for customers to deliver to their encounters with AI.

See also  Microsoft joins forces with VB Lab for 3 stops on the AI Impact Tour

What’s one of the simplest ways to responsibly construct AI?

Responsibly constructing AI requires us to broaden our notion of who performs a task in “constructing” AI. After all, influencing expertise corporations and social media platforms is a key option to have an effect on the influence of AI methods, and these establishments are important to responsibly constructing expertise. On the identical time, we should acknowledge how numerous establishments from throughout civil society, trade, media, academia and the general public should proceed to be concerned to construct accountable AI that serves the general public curiosity.

Take, for instance, the accountable improvement and deployment of artificial media.

Whereas expertise corporations is perhaps involved about their accountability when navigating how an artificial video can affect customers earlier than an election, journalists could also be fearful about imposters creating artificial movies that purport to return from their trusted information model. Human rights defenders may take into account accountability associated to how AI-generated media reduces the influence of movies as proof of abuses. And artists is perhaps excited by the chance to specific themselves via generative media, whereas additionally worrying about how their creations is perhaps leveraged with out their consent to coach AI fashions that produce new media. These numerous issues present how important it’s to contain totally different stakeholders in initiatives and efforts to responsibly construct AI, and the way myriad establishments are affected by — and affecting — the way in which AI is built-in into society.

How can traders higher push for accountable AI?

Years in the past, I heard DJ Patil, the previous chief knowledge scientist within the White Home, describe a revision to the pervasive “transfer quick and break issues” mantra of the early social media period that has caught with me. He instructed the sphere “transfer purposefully and make things better.”

I beloved this as a result of it didn’t suggest stagnation or an abandonment of innovation, however intentionality and the chance that one may innovate whereas embracing accountability. Buyers ought to assist induce this mentality — permitting extra time and area for his or her portfolio corporations to bake in accountable AI practices with out stifling progress. Oftentimes, establishments describe restricted time and tight deadlines because the limiting issue for doing the “proper” factor, and traders could be a main catalyst for altering this dynamic.

The extra I’ve labored in AI, the extra I’ve discovered myself grappling with deeply humanistic questions. And these questions require all of us to reply them.

Source link

Share This Article
Leave a comment

Leave a Reply

Your email address will not be published. Required fields are marked *