Call for Proposals: Join the ITU and Iridescent as we determine the future of AI education at the AI for Social Good Summit May 28-31

AIFC Family Challenge SubmissionSample Family Challenge project:  Uses image recognition to spot forest fires as they start and alert authorities

Family building parallel processing design challengeFamily building a hands-on project illustrating parallel processing


The world is changing dramatically as artificial intelligence (AI) is integrated into our society and work so rapidly that it is increasingly known as the 4th Industrial Revolution. Characterized by exponential rates of discovery and adoption, this revolution brings together digital, physical, and biological systems, and like the revolutions of the steam engine, electricity, and computers that preceded it, Artificial Intelligence will change our values as much as the ways we live. A shift of this magnitude will require a shift to a new economic system that accounts for basic human needs and well-being, and in turn it offers (if not demands) an immense opportunity for many different groups to be part of this movement.

Technologies such as AI are powerful tools that can unlock an individual’s potential and amplify a sense of agency and purpose. We not only need to learn more about AI, but also need to understand how to use it responsibly, and how we can improve AI technologies to create the world we wish to live in. To accomplish this, we must reimagine our approach to education.

Education needs to be seen as a lifelong journey everyone has the opportunity to pursue, and through which everyone can develop the skills needed to thrive tomorrow.

There is a need for grass-roots work with adults and children in the most vulnerable and underserved groups, to help them understand how their worlds are changing, what AI is, how some of these technologies work, and what role they can play, now and in the future.

There is a need for innovative, thoughtful, multi-generational programs that foster lifelong learning and knowledge sharing between local communities and AI experts from industry and academia.

There is a need for AI experts to work closely with media and journalists to help them demystify AI for the broader public. We need to move beyond inflammatory terms towards informed and critical debate that advances our understanding of AI’s impact on society and what needs to improve and how.

Finally, we need innovative programs and resources that help us understand the impact of AI technologies on ourselves, our brains, and our behaviors. This is where we need partnerships between bold, self-aware industry partners and neuroscientists, cognitive scientists, psychologists and educators, who can work together to design technology that is not only addictive, viral and lucrative, but also brings out the best of what humans are capable of.

Be part of the conversation about the best way to meet these needs. Submit a proposal to be part of the Education Track at the UN AI for Good Global Summit

Submit a proposal for the UN AI for Good Global Summit

Iridescent invites organizations to join in its efforts to fill important gaps in access, knowledge, agency and skills by submitting a proposal for consideration to present during the education track at the UN AI for Good Global Summit on May 29 in Geneva. Participants will also have the opportunity to be part of the working group developing the final projects launching at the end of the Summit.

Proposal submissions are due Monday, April 15, at 5p GST and should align to 1 of the 5 AI education focus areas:

  • AI in your community: Have you been involved in any initiative that increases awareness of AI technologies in the broader public? Tell us about it! What worked, what didn’t work, what did you learn? How are you going to change your program or efforts this year to make deeper impact? We would love to hear from you!
  • AI literacy in the workplace: Have you been developing or implementing any AI-literacy programs or courses in your organization for your employees or colleagues? We would love to hear what makes an engaging learning/teaching experience and your recommendations for helping people become more curious about AI. We also want to hear about any challenges that you may have encountered providing this experience at scale.
  • Demystifying AI through media: It is a challenge for journalists (especially those without technical backgrounds) to investigate highly complex and rapidly evolving AI stories in a way that doesn’t focus on sensationalist headlines. We want to hear about organizations, journalists, schools, universities that are addressing this issue in innovative ways, and what is working.
  • Our brains on AI-powered devices and games: Young or old, rich or poor, all across the world — we are all increasingly dependent on our smartphones, “daily feeds” from social media, and videogames. In particular the impact of such technologies is not understood/studied in underserved communities. We invite researchers, industry partners and community organizations to share any related work and findings that can help us all further our understanding of what is working, and what should be done next.
  • AI for lifelong learning and creating capabilities: Today AI is powering many “personalized learning systems”. We need to move beyond factual knowledge, skill development, and assessment into preparing learners to become self-driven, creative problem solvers and innovators. We invite organizations and researchers that are working on this cutting-edge technology to share what systems they have created and deployed, lessons learned and recommendations on pushing this frontier!

Submitting organizations will be notified of their selection by Monday, April 22.

Join us as we explore ways we can collectively use and apply AI to improve education in an impactful, sustainable, and ethical way.

About the Track Organizers

Tara Chklovski, the CEO & Founder of global tech education nonprofit Iridescent, is chairing the education track at the UN’s AI for Good Global Summit in Geneva. The track, titled “Reaching and Engaging 21st Century Learners” will explore how education organizations can creatively partner across industry, academia, media and policy makers to keep pace with the breathtaking advances in technology, particularly AI, to make the deepest impact in an agile, sustainable, and ethical way.

How to Demystify AI in the Classroom – Iridescent and NVIDIA at SXSWEDU

Classrooms today are no strangers to coding or robotics―but few classrooms in the US currently teach artificial intelligence, despite AI being applied across almost every industry. Seeing this need developing, in 2017 Iridescent teamed up with NVIDIA to develop a curriculum that would demystify AI for youth, teaching them real-world ways AI can be used for good and introducing them directly to AI tools they can use themselves.

Iridescent CEO Tara Chklovski and Joe Bungo, Deep Learning Institute Program Manager at NVIDIA, recently had the opportunity to discuss this collaboration and share what we’ve learned in the first year of running the AI Family Challenge at SXSWEDU.

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An Interview with Rose Luckin: Using Artificial Intelligence to Support Human Intelligence and Learning

Rose Luckin is a Professor of Learner Centered Design at the UCL Knowledge Lab in London. She researches how educational technology is designed and how it is evaluated. Professor Luckin is particularly interested in using AI to show teachers and students how people learn and how learning is cognitively, socially and emotionally shaped. She is also the Director of EDUCATE, a hub for Ed-Tech startups in London. In 2017, Rose was named on the Seldon List as one of the 20 most influential people in Education.

She recently sat down with Iridescent CEO Tara Chklovski to discuss her work with education technology, the elements of a good problem, and her advice to staying motivated in the face of setbacks.


Rose Luckin. Source: UCL

Tara Chklovski:Thank you so much for talking to me today. Tell me about the problems you work on and why you chose them.

Rose Luckin: My work is really about trying to help individual learners understand more about themselves and develop a more sophisticated understanding of where knowledge comes from, what evidence is and why they should believe something or not. And then, beyond understanding themselves in terms of their knowledge, also understanding themselves in terms of their emotions, social intelligence and awareness of their physicality in the world.

Most of what I do is trying to understand human intelligence and see how we can use artificial intelligence to help support our own intelligence. I find this increasingly involves talking to broad audiences to help people understand what AI is and what it’s good for.

That’s about half of my time. The other half of my time I spend working with startups and small and medium enterprises, some of whom are using AI to develop tools, techniques or methods that can support teaching and learning. I have a program called EDUCATE, which links startups and SMEs to researchers who are working in an area that’s relevant to them and to educators and learners for whom they are trying to develop — trying to raise the quality of the conversation around evidence and how we know if something works.

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Iridescent Announces Finalists of Debut AI World Championship

Out Of 200 Submissions, Six Families From Bolivia, Palestine, Pakistan, Spain, The United States and Uzbekistan Selected To Present Their AI Projects To Judges In Silicon Valley


Today we are proud to announce the finalists of our inaugural AI World Championship. The championship is the culmination of the AI Family Challenge, a twelve-month global learning program that brings together families, schools, communities and industry mentors so participants can learn, create and play with AI. 7,500 people from 13 countries participated in the first year of the program.

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How many types of engineer are there?

It’s Engineers Week – a chance to highlight engineers and the work they do! But there are many different types of engineers who work on solving different types of problems, using different materials. Some engineers work on the scale of huge buildings, and others work on the micro-biological level of cells and cell parts.

Learn more about five different types of engineers, what they work on, and fun projects you can do to test your own engineering skills.

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Engineers who mentor families: Exploring Artificial Intelligence in Coimbatore, India

It’s National Engineers Week! National Engineers Week is an opportunity to celebrate engineers and their work. In particular, we like to focus on celebrating the amazing engineers who mentor students and families and share their passion and expertise with learners around the world.

Meet Vigneshwer, a data scientist in Coimbatore, India. Vigneshwer volunteered as a mentor for the AI Family Challenge this year, where he worked with local students and their families and taught them about artificial intelligence. Inspired to help people move beyond seeing AI as a “black box they’re not really familiar with” to understanding the ways AI is a tool they can use to make their lives better, Vigneshwar guided families through hands-on projects and lessons about AI concepts and tools, and hoped that they would also tap into their curiosity to keep learning beyond the program.

“You need to learn continuously…that’s the most important thing as a human that you need to do.”

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Machine Learning and Medicine: An Interview with Daphne Koller

Daphne Koller leads Insitro, a company applying machine learning to pharmaceutical drug development. She is also a co-founder of Coursera (one of the world’s largest online education platforms with 30 million + users), a MacArthur Fellowship recipient, and Computer Science Professor at Stanford University.

Recently, she discussed machine learning in the biomedical industry as well as what she thinks are vital characteristics to achieve individual success with Iridescent CEO & Founder Tara Chklovski.

Daphne Koller

Tara Chklovski (TC): Can you share two of the most interesting problems that you’ve tried to tackle in your career and what you’re working on now?

Daphne Koller (DK): My work cuts across a variety of fields including biomedical, education, and problems like computer vision. There are two specific biomedical projects I’m very proud of. The first one involved working with a neonatologist, a doctor for premature babies, to predict survival rates for neonates. Neonates are premature, teeny babies – they’re about the size of your hand and weigh less than 200 grams. They often struggle to survive. The doctor and I worked together to predict the risk of death for these babies. Our hope was to help doctors identify and help the babies at highest risk survive. In our study we didn’t rely on the traditional tests for babies’ health (which we found don’t work well for babies born that early), and we didn’t want to rely on invasive measures like sticking these tiny babies with needles! So we used the data from the bedside monitor. The bedside monitor measures things like the baby’s heart rate, respiratory rate, and their oxygen saturation. It turns out that there are markers in that non-invasive data that can predict survival rates, and that you don’t need that much data to make useful recommendations. We were able to make predictions based on data collected from the first few days of the baby’s life.

Source: Science/AAAS;
Example of tumor images that have been stained and then labeled to identify more aggressive tumors.

Another project I did with a PhD student of mine who was an MD/PhD pathologist. We were looking at images of tumors from breast cancer patients and trying to predict five-year survival rates to help organize patients by risk. We took a data-driven approach. Pathologists have been looking at these sort of images for a century. For our project, we included more features in our dataset than the standard features pathologists consider. We put in everything that we could think of, including hundreds of features that no one has ever looked at before. As a result, our predictions were better than pathologists’, and the features that were being used by our predictor were quite different from the ones that pathologists had been looking at. Specifically, they had been looking at features of the tumor cells, and it turned out that the features of the cells that surround the tumor were actually more predictive! Today, this is well recognized as a critical factor in cancer survival, and is called the tumor microenvironment. This microenvironment where cancer lives, and the immune system are factors that are absolutely critical in cancer patient survival. Our paper was one of the earliest pieces of evidence supporting that.

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5 Women You Should Know Working in AI

AI is changing the world – everything from the way we shop for groceries to the way we hire people for jobs, but it doesn’t really reflect the world it’s changing. Wired estimates that only 12% of leading machine learning researchers are women, and we know that a lack of diverse AI researchers means that the technology they build skews towards a white and male default representation of the world, effectively reproducing and worsening existing human bias.

The technology that’s shaping our future needs to be built by people who represent the diversity of humanity, in order to ensure that the future is designed for all of us. Today we’ll start highlighting the many amazing women already doing inspiring work with Artificial Intelligence. In the first of a series highlighting women using technology to solve big problems, here are 5 women in AI you should know, sharing their work, their inspiration, and how they find problems they want to solve.

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