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Women in AI: Urvashi Aneja is researching the social impact of AI in India | Prime Time News24


To offer AI-focused girls teachers and others their well-deserved — and overdue — time within the highlight, Prime Time News24 is launching a sequence 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.

Urvashi Aneja is the founding director of Digital Futures Lab, an interdisciplinary analysis effort that seeks to look at the interplay between know-how and society within the World South. She’s additionally an affiliate fellow on the Asia Pacific program at Chatham Home, an Prime Time News24 coverage institute primarily based in London.

Aneja’s present analysis focuses on the societal impression of algorithmic decision-making programs in India, the place she’s primarily based, and platform governance. Aneja not too long ago authored a research on the present makes use of of AI in India, reviewing use circumstances throughout sectors together with policing and agriculture.

Q&A

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

I began my profession in analysis and coverage engagement within the humanitarian sector. For a number of years, I studied using digital applied sciences in protracted crises in low-resource contexts. I shortly discovered that there’s a wonderful line between innovation and experimentation, significantly when coping with susceptible populations. The learnings from this expertise made me deeply involved concerning the techno-solutionist narratives across the potential of digital applied sciences, significantly AI. On the identical time, India had launched its Digital India mission and Nationwide Technique for Synthetic Intelligence. I used to be troubled by the dominant narratives that noticed AI as a silver bullet for India’s advanced socio-economic issues, and the whole lack of important discourse across the concern.

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

I’m proud that we’ve been ready to attract consideration to the political economic system of AI manufacturing in addition to broader implications for social justice, labor relations and environmental sustainability. Fairly often narratives on AI give attention to the positive aspects of particular functions, and at greatest, the advantages and dangers of that utility. However this misses the forest for the timber — a product-oriented lens obscures the broader structural impacts such because the contribution of AI to epistemic injustice, deskilling of labor and the perpetuation of unaccountable energy within the majority world. I’m additionally proud that we’ve been capable of translate these considerations into concrete coverage and regulation — whether or not designing procurement pointers for AI use within the public sector or delivering proof in authorized proceedings in opposition to Huge Tech corporations within the World South.

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

By letting my work do the speaking. And by consistently asking: why?

What recommendation would you give to girls in search of to enter the AI subject?

Develop your information and experience. Be sure that your technical understanding of points is sound, however don’t focus narrowly solely on AI. As a substitute, research extensively in an effort to draw connections throughout fields and disciplines. Not sufficient individuals perceive AI as a socio-technical system that’s a product of historical past and tradition.

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

I feel probably the most urgent concern is the focus of energy inside a handful of know-how corporations. Whereas not new, this drawback is exacerbated by new developments in massive language fashions and generative AI. Many of those corporations are actually fanning fears across the existential dangers of AI. Not solely is that this a distraction from the present harms, but it surely additionally positions these corporations as obligatory for addressing AI-related harms. In some ways, we’re shedding a few of the momentum of the “tech-lash” that arose following the Cambridge Analytica episode. In locations like India, I additionally fear that AI is being positioned as obligatory for socioeconomic growth, presenting a chance to leapfrog persistent challenges. Not solely does this exaggerate AI’s potential, but it surely additionally disregards the purpose that it isn’t attainable to leapfrog the institutional growth wanted to develop safeguards. One other concern that we’re not contemplating critically sufficient is the environmental impacts of AI — the present trajectory is more likely to be unsustainable. Within the present ecosystem, these most susceptible to the impacts of local weather change are unlikely to be the beneficiaries of AI innovation.

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

Customers should be made conscious that AI isn’t magic, nor something near human intelligence. It’s a type of computational statistics that has many helpful makes use of, however is finally solely a probabilistic guess primarily based on historic or earlier patterns. I’m certain there are a number of different points customers additionally want to concentrate on, however I wish to warning that we ought to be cautious of makes an attempt to shift duty downstream, onto customers. I see this most not too long ago with using generative AI instruments in low-resource contexts within the majority world — slightly than be cautious about these experimental and unreliable applied sciences, the main target usually shifts to how end-users, akin to farmers or front-line well being staff, have to up-skill.

What’s the easiest way to responsibly construct AI?

This should begin with assessing the necessity for AI within the first place. Is there an issue that AI can uniquely remedy or are different means attainable? And if we’re to construct AI, is a posh, black-box mannequin obligatory, or may a less complicated logic-based mannequin do exactly as effectively? We additionally have to re-center area information into the constructing of AI. Within the obsession with huge information, we’ve sacrificed principle — we have to construct a principle of change primarily based on area information and this ought to be the premise of the fashions we’re constructing, not simply huge information alone. That is in fact along with key points akin to participation, inclusive groups, labor rights and so forth.

How can traders higher push for accountable AI?

Traders want to contemplate the whole life cycle of AI manufacturing — not simply the outputs or outcomes of AI functions. This may require taking a look at a spread of points akin to whether or not labor is pretty valued, the environmental impacts, the enterprise mannequin of the corporate (i.e. is it primarily based on business surveillance?) and inner accountability measures inside the firm. Traders additionally have to ask for higher and extra rigorous proof concerning the supposed advantages of AI.

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