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To giveAI - focused womenacademics and others their well - deserved — and delinquent — metre in the spotlight , TechCrunch is launching aseries of interviewsfocusing on remarkable charwoman who ’ve contributed to the AI gyration . We ’ll publish several piece throughout the year as the AI windfall continues , highlighting key work that often extend unrecognised . Read more profileshere .
Kristine Gloria formerly led the Aspen Institute ’s Emergent and Intelligent Technologies Initiative — the Aspen Institute being the D.C.-headquartered think tankful focused on values - free-base leadership and policy expertise . Gloria holds a PhD in cognitive scientific discipline and a Master ’s in media studies , and her retiring employment includes enquiry at MIT ’s Internet Policy Research Initiative , the San Francisco - base Startup Policy Lab and the Center for Society , Technology and Policy at UC Berkeley .
Q&A
concisely , how did you get your starting time in AI ? What draw you to the field ?
To be frank , I definitely did n’t start my vocation in pursuit of being in AI . First , I was really interested in empathize the intersection of technology and public insurance policy . At the time , I was work on my Master ’s in spiritualist studies , exploring ideas around remix culture and intellectual place . I was living and work in D.C. as an Archer Fellow for the New America Foundation . One mean solar day , I clearly commend sit in a room fill with public policymakers and political leader who were throwing around terms that did n’t quite fit their real technical definition . It was shortly after this confluence that I realized that for move the needle on public policy , I needed the credentials . I hold up back to school , earning my doctor’s degree in cognitive scientific discipline with a concentration on semantic technologies and online consumer concealment . I was very rosy to have find a wise man and advisor and research laboratory that further a ill-tempered - disciplinary discernment of how technology is design and build up . So , I sharpen my proficient skills alongside developing a more critical viewpoint on the many way tech intersect our lifespan . In my role as the director of AI at the Aspen Institute , I then had the prerogative to ideate , lock and collaborate with some of the direct thinker in AI . And I always found myself gravitating towards those who took the time to deep query if and how AI would impact our day - to - day lives .
Over the age , I ’ve leave various AI first step and one of the most meaningful is just getting started . Now , as a founding squad member and director of strategical partnerships and innovation at a fresh nonprofit , Young Futures , I ’m excited to weave in this type of thinking to accomplish our delegacy of constitute the digital world an easier place to grow up . Specifically , as productive AI becomes table bet and as new applied science do online , it ’s both urgent and critical that we help preteen , teens and their livelihood whole pilot this huge digital wilderness together .
What work are you most lofty of ( in the AI field ) ?
I ’m most proud of two go-ahead . First is my work pertain to surfacing the tensions , pit and essence of AI on marginalize communities . Published in 2021 , “ Power and Progress in Algorithmic Bias ” articulate month of stakeholder engagement and research around this upshot . In the report , we fix one of my all - fourth dimension favorite question : “ How can we ( datum and algorithmic wheeler dealer ) recast our own models to forecast for a different hereafter , one that centers around the needs of the most vulnerable ? ” Safiya Noble is the original author of that question , and it ’s a constant considerateness throughout my study . The second most of import initiative of late came from my fourth dimension as head word of Data at Blue Fever , a ship’s company on the commission to amend youth well - being in a judgment - loose and inclusive online place . Specifically , I led the design and development of Blue , the first AI aroused reinforcement companion . I learned a lot in this process . Most saliently , I gained a profound raw admiration for the impact a virtual companion can have on someone who ’s scramble or who may not have the funding systems in place . Blue was designed and built to land its “ big - sibling energy ” to avail guide user to reflect on their genial and excited needs .
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How do you pilot the challenges of the male - dominated tech diligence , and , by annex , the male person - reign AI manufacture ?
Unfortunately , the challenges are real and still very current . I ’ve experience my average contribution of disbelief in my skills and experience among all type of colleagues in the blank . But , for every individual one of those electronegative challenges , I can point to an model of a manly colleague being my vehement cheerleader . It ’s a bad surround , and I hold up on to these instance to help oneself supervise . I also think that so much has changed in this blank even in the last five years . The necessary science set and professional experiences that qualify as part of “ AI ” are not strictly computer science - focused anymore .
What advice would you give to adult female seeking to enter the AI field ?
Enter in and follow your curiosity . This space is in constant apparent movement , and the most interesting ( and likely most fertile ) pursuit is to continuously be critically optimistic about the field itself .
What are some of the most pressing issues face AI as it evolves ?
I in reality think some of the most pressing issues face AI are the same issues we ’ve not quite gotten right since the web was first usher in . These are effect around agency , autonomy , privacy , fairness , equity and so on . These are core to how we situate ourselves amongst the simple machine . Yes , AI can make it vastly more complicated — but so can socio - political shifts .
What are some issue AI user should be mindful of ?
AI users should be aware of how these arrangement rarify or enhance their own agency and autonomy . In addition , as the discourse around how technology , and especially AI , may touch our well - being , it ’s important to remember there are tried - and - true tools to pull off more disconfirming outcomes .
What is the best way to responsibly build AI ?
A responsible build of AI is more than just the computer code . A truly creditworthy build takes into account the design , governing , policies and business organization model . All drive the other , and we will preserve to precipitate short if we only strive to address one part of the build .
How can investors better push for responsible for AI
One specific labor , which I admire Mozilla Ventures for requiring in its diligence , is an AI example card . Developed by Timnit Gebru and others , this practice of creating modelling cards enables teams — like funders — to assess the risks and safety outcome of AI fashion model used in a organization . Also , related to the above , investors should holistically valuate the scheme in its capacity and power to be built responsibly . For instance , if you have trust and prophylactic feature in the form or a model board published , but your tax income model exploits vulnerable population data , then there ’s misalignment to your intent as an investor . I do think you may build responsibly and still be profitable . Lastly , I would love to see more collaborative financial support opportunity among investors . In the kingdom of well - being and mental wellness , the solutions will be wide-ranging and vast as no person is the same and no one solution can clear for all . Collective legal action among investor who are interested in lick the problem would be a welcome improver .
