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To giveAI - concentre womenacademics and others their well - deserved — and overdue — time in the spot , TechCrunch has been put out aseries of interviewsfocused on singular women who ’ve contributed to the AI rotation . We ’re publish these bit throughout the year as the AI bonanza continues , spotlight key work that often run unrecognized . Read more profileshere .
In the spotlight today : Anna Korhonen is a professor of natural language processing ( NLP ) at theUniversity of Cambridge . She’salso a senior research dude atChurchill College , a fellow at the Association for Computational Linguistics , and a familiar at the European Laboratory for Learning and Intelligent Systems .
Korhonen previously serve as a mate at theAlan Turing Institute and she has a PhD in computer skill and master ’s degrees in both information processing system science and philology . She search NLP and howto originate , adapt and apply computational techniques to meet the motive of AI . She has a finical interestin responsible and “ human - centrical ” NLP that — in her own words — “ draws on the understanding of human cognitive , societal and originative intelligence . ”
Q&A
in brief , how did you get your head start in AI ? What attracted you to the subject area ?
I was always bewitch by the beauty and complexity of human intelligence , particularly in congress to human language . However , my pursuit in STEM subjects and practical applications lead me to hit the books technology and computer science . I chose to specialize in AI because it ’s a field that allows me to combine all these interests .
What work are you most gallant of in the AI field ?
While the science of ramp up intelligent machines is bewitching , and one can easily get lost in the man of speech model , the ultimate reason we ’re building AI is its virtual potential difference . I ’m most lofty of the employment where my fundamental research on natural language processing has lead into the ontogeny of tools that can corroborate social and global good . For deterrent example , tools that can help us advantageously understand how diseases such as cancer or dementia develop and can be deal , or apps that can hold instruction .
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Much of my current research is drive by the mission to get AI that can improve human life for the good . AI has a huge positive potential difference for social and global good . A big part of my job as an pedagogue is to advance the next contemporaries of AI scientists and leader to sharpen on realizing that potential .
How do you pilot the challenges of the male - dominated tech diligence and , by file name extension , the male person - command AI industry ?
I ’m golden to be working in an area of AI where we do have a sizable distaff population and established support connection . I ’ve found these immensely helpful in navigating career and personal challenges .
For me , the biggest problem is how the male - dominated industry coiffe the agenda for AI . The current weapons system subspecies to develop ever - big AI models at any cost is a bully example . This has a huge encroachment on the priority of both academe and industry , and wide - ranging socioeconomic and environmental implications . Do we call for larger mannikin , and what are their planetary price and benefit ? I feel we would ’ve asked these questions a lot originally in the game if we had better sexuality balance in the field .
What advice would you give to woman seeking to enter the AI field ?
AI desperately needs more womanhood at all levels , but particularly at the level of leadership . The current leaders cultivation is n’t inevitably attractive for women , but active liaison can change that culture — and ultimately the culture of AI . woman are infamously not always nifty at supporting each other . I would really wish to see an position change in this respectfulness : We need to actively internet and help each other if we want to achieve unspoilt sex balance in this battlefield .
What are some of the most pressing issues face AI as it germinate ?
AI has developed implausibly fast : It has acquire from an pedantic field to a global phenomenon in less than a single decade . During this time , most effort has gone toward scale through monumental data and computation . Little effort has been devote to recall how this technology should be develop so that it can well serve humans . People have a unspoiled understanding to care about the safety and trustiness of AI and its impingement on job , commonwealth , environment and other areas . We demand to desperately put human needs and safety at the center of AI maturation .
What are some issue AI user should be aware of ?
Current AI , even when seeming extremely silver , at last miss the existence knowledge of humanity and the ability to sympathise the complex societal contexts and norms we operate with . Even the best of today ’s applied science makes mistakes , and our power to forestall or augur those mistake is limited . AI can be a very useful tool for many tasks , but I would not commit it to educate my children or make important determination for me . We humans should remain in charge .
What is the good mode to responsibly build AI ?
Developers of AI tend to consider about ethical code as an reconsideration — after the engineering has already been built . The best way to think about it isbeforeany maturation begin . Questions such as , “ Do I have a diverse enough squad to prepare a just system ? ” or “ Is my information really free to use and example of all the exploiter ’ universe ? ” or “ Are my techniques robust ? ” should really be ask at the first .
Although we can come up to some of this problem via training , we can only enforce it via regulation . The recent growing of national and global AI regulations is authoritative and needs to bear on to guarantee that next technology will be safer and more trusty .
How can investor better promote for responsible AI ?
AI regulating are come forth and companies will ultimately need to abide by . We can think of responsible AI as sustainable AI truly worth investing in .
