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To giveAI - focalize womenacademics and others their well - deserved — and delinquent — time in the public eye , TechCrunch has been publish aseries of interviewsfocused on remarkable women who ’ve contributed to the AI gyration . We ’re publishing these composition throughout the year as the AI boom continues , highlighting fundamental work that often goes unrecognized . Read more profileshere .
Chinasa T. Okolois afellow at the Brookings Institutionin the Center of Technology Innovation ’s Governance Studies plan , and in September 2024 was named one of the100 most influential people in AI by Time . Before Brookings , she serve on the value orientation and social impact citizens committee that helped develop Nigeria ’s National Artificial Intelligence Strategy and has served as an AI policy and ethics consultant for various organizations , let in the African Union Development Agency and the Quebec Artificial Intelligence Institute . She late received a PhD in estimator scientific discipline from Cornell University , where she researched how AI touch the Global South .
Briefly , how did you get your start in AI ? What draw you to the field ?
I initially transitioned into AI because I saw how computational techniques could advance biomedical research and democratise admission to health care for marginalized community . During my last year of undergrad [ at Pomona College ] , I began research with a human - computer interaction prof , which exposed me to the challenge of prejudice within AI . During my PhD , I became concerned in empathise how these issues would impact multitude in the Global South , who represent a absolute majority of the earth ’s universe and are often turf out from and underrepresented in AI development .
What work are you most lofty of in the AI field ?
I ’m incredibly proud of my work with the African Union ( AU ) on developing the AU - AI Continental Strategy for Africa , which aims to aid AU member states prepare for the responsible for adoption , development , and governance of AI . The draftsmanship of the scheme took over 1.5 old age and was release in former February 2024 . It is now in an open feedback geological period with the end of being formally take over by AU appendage nation in other 2025 .
As a first - generation Nigerian American who turn up in Kansas City , Missouri , and did n’t leave the States until study abroad during undergraduate , I always aimed to center my calling within Africa . engage in such impactful work so early in my calling makes me excited to pursue similar opportunity to help shape inclusive , global AI governance .
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How do you voyage the challenges of the male - dominate tech industry and , by extension , the male person - master AI industry ?
Finding community with those who divvy up my value has been essential in navigate the male person - dominate tech and AI industries .
I ’ve been rosy to see many overture in creditworthy AI and prominent research reveal the harms of AI being lead by grim women scholar like Timnit Gebru , Safiya Noble , Abeba Birhane , Ruha Benjamin , Joy Buolamwini , and Deb Raji , many of whom I ’ve been able to link with over the past few years .
determine their leadership has actuate me to continue my work in this field and shown me the note value of going “ against the grain ” to make a meaningful impact .
What advice would you give to women seeking to enter the AI field ?
Do n’t be restrain by a lack of a expert background . The field of AI is multi - dimensional and needs expertness from various arena . My inquiry has been influenced intemperately by sociologists , anthropologists , cognitive scientist , philosopher , and others within the humanities and societal sciences .
What are some of the most pressing issues face AI as it evolve ?
One of the most spectacular issues will be improving the equitable representation of non - Western cultures in prominent language and multimodal modelling . The vast majority of AI models are trained in English and on data that primarily represents Western contexts , which leave out valuable perspectives from the absolute majority of the earth .
to boot , the race toward building larger models will top to a higher depletion of natural resources and smashing climate change impacts , which already disproportionately impact Global South countries .
What are some issues AI drug user should be aware of ?
A significant turn of AI tools and systems that have been put into public deployment overstate their capabilities and simply do n’t function . Many tasks people aim to use AI for could likely be clear through simpler algorithms or basic automation .
Additionally , reproductive AI has the capacity to exacerbate damage observed from earlier AI tools . For age , we ’ve seen how these tools march bias and result to harmful decision - qualification against vulnerable community , which will likely increase as generative AI grows in scale leaf and get through .
However , enabling masses with the noesis to understand the limitations of AI may help meliorate the responsible for adoption and utilisation of these cock . Improving AI and data literacy within the general public will become fundamental as AI cock rapidly become integrated into guild .
What is the estimable way to responsibly build AI ?
The sound mode to responsibly ramp up AI is to be vital of the intended and unintended use guinea pig for these dick . masses building AI arrangement have the responsibility to object to AI being used for harmful scenarios in warfare and policing and should seek external guidance if AI is appropriate for other use face they may be targeting . give that AI is often an amplifier of existing societal inequalities , it is also imperative that developers and research worker be conservative in how they build and curate datasets that are used to train AI role model .
How can investors better bear on for responsible AI?Many argue that rising VC interest in “ cashing out ” on the current AI wave has accelerated the rise of “ AI snake oil colour , ” [ a term ] strike by Arvind Narayanan and Sayash Kapoor . I agree with this sentiment and believe that investors must take leadership positions , along with academics , civil lodge stakeholder , and diligence member , to advocate for responsible AI development . As an Angel Falls investor myself , I have see many dubious AI tools on the marketplace . investor should also invest in AI expertness to veterinarian companies and request international audit of tools demoed in rake decks .
Anything else you wish well to tot ?
This on-going “ AI summer ” has led to a proliferation of “ AI experts ” who often detract from important conversation on present - day risks and impairment of AI and present shoddy information on the capabilities of AI - enabled tool . I encourage those interested in train themselves on AI to be critical of these voices and assay reputable sources to learn from .
