Meet the Shapers building the future of Artificial Intelligence
This year a handful of us in the San Francisco hub kicked off a new project, AI: Re-coding our Future, to survey the field of AI in diversity, education, and policy and bridge the gap between experts and those new to the field. As part of the project, we are focusing on the phenomenal work being done by Shapers from around the globe.
More often than not, many people look to Silicon Valley as the epicenter of technology and innovation. Yet, what many fail to realize is that there’s also groundbreaking work and research being done outside of Silicon Valley. SF Shaper, Maricel Saenz, put forth the idea to showcase Global Shapers working in various roles within AI in a Humans of New York-style profile — and now we’re excited to share this amazing group of Shapers.
Abhishek Gupta, Founder of Montreal AI Ethics Institute & Machine Learning Engineer at Microsoft
🤓What are you working on?
Abhishek’s research focuses on applied technical and policy methods to address ethical, safety and inclusivity concerns in using AI in different domains. He has built the largest community driven, public consultation group on AI Ethics in the world that has made significant contributions to the Montreal Declaration for Responsible AI, the G7 AI Summit and the European Commission Trustworthy AI Guidelines. His work on public competence building in AI Ethics has been recognized by governments from North America, Europe and Asia. More information on his work can be found at his GitHub profile or at the Montreal AI Ethics Institute page.
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🤖How did you get into AI?
It started with my first course in AI at McGill University with the prolific Professor Joelle Pineau!
🤔How do you see the role of AI in the future?
AI’s role in the future treads a fine line at the moment where it stands to bring a tremendous set of benefits in terms of improvements in quality of life and helping us solve some of our biggest societal challenges. Yet, there are a lot of concerns in the way these systems are being deployed indiscriminately today, especially without regards to the ethical, safety and inclusion issues that arise in the use of these systems in places where they have significant impacts on human lives. It is our duty to take the time to understand these issues and work with a diversity of people to bring meaningful solutions to mitigate these potential harms and maximize the potential benefits
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📚What are the best resources for those that want to learn more about AI?
For folks looking to learn more about AI ethics, I’d encourage you to take a look at Montreal AI Ethics Institute’s Blog.
Tuomas Ylä-Kauttu, Director of Growth & Partnerships at Etsimo Healthcare
🤓What are you working on?
I’m now focusing on the UN’s SDG 3 by keeping people healthy via an AI doctor platform called Etsimo Healthcare. Our mission is to help everyone to stay healthy, sustain a high quality of life and prevent irreversible chronic conditions.
🤖How did you get into AI?
I have always been a great believer in science and technology. In my previous work as a management consultant I gained a lot of exposure to different exponential technologies. I followed my natural curiosity and the more I studied the phenomenon of AI, the more I understood the growing importance and impact of the technology. I figured that it would be great to apply this technology into a field with a lot of potential for creating impact like healthcare. I made a few very early stage attempts to build a startup without much success. Along the way, the opportunity to join Etsimo Healthcare came about and I was immediately excited. Many of the concepts and thinking I had put into the startups actually were aligned at Etsimo so I felt I had finally found home.
🤔How do you see the role of AI in the future?
I see that AI plays a vital role in solving many of the UN SDGs and should be applied to the greatest challenges that we are facing today including climate change, healthcare and education.
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📚What are the best resources for those that want to learn more about AI?
1. Books:
Topol — Deep Medicine
Tegmark — Life 3.0
Lee — AI Superpowers
Brynjolfsson — Machine Platform Crowd
Harari — Homo Sapiens + Deus + 21 Lessons
Bostrom — Superintelligence⠀⠀
2. Podcasts:
Andreessen Horowitz’ Blog on Machine Learning and AI Playbook
3. Courses:
Elements of AI for basics
Coursera
Udemy + many universities have MOOCs
Renjie Butalid, Co-founder & Associate Director of Montreal AI Ethics Institute
🤓What are you working on?
Building public competence and understanding on the societal impacts of AI through my work with the Montreal AI Ethics Institute.
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🤖How did you get into AI?
I’ve been working at the intersection of technology startups, social innovation and cross-sector civic engagement for over a decade. My work in AI right now focuses on facilitating and building public methods to evaluate and assess AI for bias − AI for the public good must include the public.
🤔How do you see the role of AI in the future?
While we are still years away from artificial general intelligence and doomsday scenarios often depicted in Hollywood movies, concrete issues such as fairness, bias, transparency, accountability, reproducibility and explainability need to be addressed right now, in order to ensure the meaningful development of AI solutions that are ethical, safe and inclusive.
📚What are the best resources for those that want to learn more about AI?
1. Jack Clark’s Import AI e-newsletter⠀⠀
2. Will Knight and Karen Hao’s work at MIT Technology Review ⠀⠀
3. Andrew Ng’s AI for Everyone course on Coursera
Sofia Gavefak, Program Manager & Project Leader at
AI Sustainability Center
🤓What are you working on?
As a Program Manager / Project leader at AI Sustainability Center — a multi disciplinary center/hub aimed at developing and implementing frameworks and tools that help organisations manage the societal / ethical risks of AI.
🤖How did you get into AI?
My first “contact” with AI was in its mathematical form as I studied the “math” behind machine learning at university. Later, working as a management consultant after graduation I did some projects with our data scientist teams where predictive analytics was at core. Today I work full time with researchers and data scientists in fields of AI & ethics.
🤔How do you see the role of AI in the future?
My dream scenario is that AI will be a power ful tool for augmented humans, witch internationally agreed regulations for some applications of it.⠀
📚What are the best resources for those that want to learn more about AI?
1. Newsletter: MIT Tech Review’s The Algorithm
2. Courses: New York University, Center for Data Science, Spring 2019.
Vytautas Mikalainis, Software Engineer at Sermo and Co-Founder of Vilnius City AI community
🤓What are you working on?
Working in data collecting company, but also I had an AI chatbot startup and currently I am working with fintech startup, Sermo.
🤖How did you get into AI?
I am co-founder of Vilnius City AI community, where we organize quarterly events.
🤔How do you see the role of AI in the future?
I will be studying Artificial Intelligence from September in Edinburgh University, so I want to work as AI or machine learning engineer in the future. And I want to make stronger local community in my city.
📚What are the best resources for those that want to learn more about AI?
Currently I am getting all information from city AI network we are sharing various books, podcasts and etc. Also participating in my city’s AI community meetups, there are 3 communities and various types, from professional till educational.
Chuy Cepeda, Co-Founder & CEO at OS City
🤓What are you working on?
Improving governments’ efficiency and trust. Leveraging the newest technologies to transform governments into platforms of digital services.⠀
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🤖How did you get into AI?
I completed a Ph.D. in Robotics and AI
🤔How do you see the role of AI in the future?
As the world wide web in the 90s, accessible, democratized, with a promising boom. I see a lot of humanity on top of AI in the future, hopefully, more of the good one and less of the bad one…
📚What are the best resources for those that want to learn more about AI?
Go here for the best resources in Machine Learning & AI
Learn more about Chuy (here) or OS City (here).
Lauren “Lorny” Pfeifer, Venture Capital Investor at MGV, EECS Student, and Creator of Machines+Intelligence
🤓What are you working on?
By day I am a VC investor. By all other hours I am studying electrical engineering and computer science (part-time). I’m also the creator behind a blog called Machines+Intelligence, which focuses on AI/robotics ecosystems around the globe. I also run the Bay Area Deep Reinforcement Learning meetup.
🤖How did you get into AI?
Back in 2013, I was severely depressed and wanted so badly to learn something new. So I taught myself Python, started building basic robots. After a couple of years, I was a NASA (NCAS) Aerospace Scholar and met the Chief Scientist of Armstrong Flight Research Institute. He told me that machine learning is the future and to acquire knowledge in this field. So I took Andrew Ng’s Machine Learning course, read as many books on artificial intelligence as I could. Fast forward to 2017, my engineering professor told me to apply for the Fast.AI Deep Learning Diversity Fellows program. Since then I’ve become incredibly fascinated with machine learning, deep learning, and now especially deep reinforcement learning applied to robotics and have been building my own projects like an anxiety attack chatbot, image classifiers, and most recently working with robotics in simulated environments.
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🤔How do you see the role of AI in the future?
I think it will be part of our everyday lives — similar to how software was a new innovation back in the day and is now commonplace. I am excited to see how the developments of machine learning can help with disease diagnosis, innovate in robotics and autonomous vehicles.
📚What are the best resources for those that want to learn more about AI?
Andrew Ng’s AI for Everyone course to learn about the every day applications. For those without quantitative backgrounds, I suggest taking Berkeley’s online Python Programming course, then move onto Python for Data Science and Machine Learning bootcamp (Udemy), then do Andrew Ng’s Stanford ML course. If you’re curious about the policy aspects of AI, I recommend Marc Rotenberg’s AI Policy Sourcebook 2019.
Prajit Datta, AI Research Scientist at ÅF Pöyry
🤓What are you working on?
I’m currently working on Smart Surveillance Systems.
🤖How did you get into AI?
I started reading about it from college days. Learned R Programming and read books on machine learning algorithms. Eventually, I got a job as a data scientist after graduation in one of the leading MNC.
🤔How do you see the role of AI in the future?
Very promising, Our ecosystem is going to change.
📚What are the best resources for those that want to learn more about AI?
I recommend Coursera and EDX courses, Data science Central and Analytics Vidhya Blog, Kaggle competitions
Learn more about Prajit here.
Pritika Mehta, Founder of SockSoho
🤓What are you working on?
I am the founder of SockSoho, a direct-to-consumer fashion brand for men. At SockSoho we make data-driven decisions at every level, from marketing to operations to product design.
🤖How did you get into AI?
Since childhood the only subject that fascinated me was Mathematics. I could not think of a career for myself that did not involve mathematics.
On 2013, Machine Learning and AI were becoming popular. I read a lot about it on Quora and blogs. I realized that ML is very heavy on Mathematics and maybe I should give it a try.
So, every night after my job I used to grab my laptop and watch Andrew Ng Stanford class on Youtube. I became very fascinated with the power of data; how things can be predicted with statistics and coding applied to data.
That’s when I decided to pursue a Masters in AI and make my career in it.
Then, got the chance to work with Bank of America in Manhattan and Tripadvisor in Boston.
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🤔How do you see the role of AI in the future?
AI will be integrated at every level of our life within the next 10 years. Use of AI will help us take lesser decisions since our habits/behavior will be easily predicted by software integrated on our phone.
A lot of jobs will become non-existent and a lot of new creative jobs will be created. In fact, I spoke about it in detail in my TEDx talk
📚What are the best resources for those that want to learn more about AI?
Courses
Intro to Machine Learning — Udacity
Intro to Machine learning by Andrew Ng — Coursera
Books
Pattern Recognition and Machine Learning — Christopher Bishop
Machine Learning Yearning — Andrew Ng
Quora has tons of information available on different topics as well.
Harry Goldberg, MPH/MBA Graduate Student at UC Berkeley, Haas School of Business
🤓What are you working on?
Advising various healthcare AI startups. Participating in the United States’ Centers for Medicare & Medicaid Services (CMS) AI Health Outcomes Challenge to build an AI/Deep Learning model to predict unplanned hospital admissions and other adverse events.
🤖How did you get into AI?
After moving to the Bay Area to become a graduate student, I was surrounded by health industry news about the impact of AI, and I was coincidentally located on a university campus with some of the top AI researchers in the world.
🤔How do you see the role of AI in the future?
It will meaningfully increase the quality and decrease the cost of making predictions.
📚What are the best resources for those that want to learn more about AI?
For a high-level understanding of AI through the lens of economics and business strategy, read Prediction Machines by Joshua Gans, Avi Goldfarb, Ajay Agrawal. To see the current and emerging use cases of AI in healthcare, read Deep Medicine by Eric Topol. I also read related email newsletters from Dr. Penguin, CB Insights, CognitionX, and AI Industry Weekly.
WANT TO BE FEATURED? If you are a Global Shaper working in artificial intelligence and want to be featured as a Shaper of AI, ping us on Instagram or Twitter.
LEARN MORE ABOUT THE PROJECT - AI: Re-Coding our Future, check out the project website. We have some exciting plans for 2020 including panels with experts in AI diversity, education, and policy, along with a massive resource library on all things AI, and a Mentorship Program for Women in AI.
