How we learned to break down barriers to machine learning

Welcome to the week after Ars Frontiers! This article is the first in a short series of articles that will summarize each of the daily presentations for those who were unable to travel to the District of Columbia for our first conference. We’ll be running one of them every few days for the next few weeks, and each one will include a built-in video of the speech (along with a transcript).

For today’s summary, we speak with Amazon Web Services technology evangelist Dr. Nashley Sefus. Our discussion was entitled “Breaking Barriers to Machine Learning”.

What are the barriers?

Dr. Sefus came to AWS by a detour, grew up in Mississippi, before eventually joining a technology startup called Partpic. Partpic was an artificial intelligence and machine learning (AI / ML) company with a neat premise: users could take pictures of tools and parts, and the Partpic app algorithmically analyzed photos, identified a detail, and provided information on what that detail was. was and where to buy more. Partpic was acquired by Amazon in 2016, and Dr. Sefus transferred his machine learning skills to AWS.

When asked, she recognized access as the biggest hurdle to greater use of AI / ML – in many ways this is another wrinkle in the old problem digital divide. The main component of the ability to use the most common AI / ML tools is reliable and fast Internet access and based on her experience, Dr. Sefus noted that the lack of access to technology in primary schools in poor areas of the country prevents children from using those tools. of which we speak.

In addition, lack of early access leads to resistance to technology later in life. “You’re talking about a concept that a lot of people think is pretty scary,” she explained. “Many people are afraid. They are threatened by technology. “

Indivisible things

One way to combat the difference here, in addition to simply increasing access, is to change the way technologists communicate to ordinary people on complex topics like AI / ML. “I understand that, as technologists, we many times just love to build cool things, right?” Said Dr. Sefus. “We don’t think about long-term impact, but that’s why it’s so important to have such a variety of ideas and different points of view at the table.”

Dr Sefus said AWS is hiring sociologists and psychologists to join its technical teams to figure out ways to tackle the digital divide by meeting people where they are, rather than forcing them to turn to technology.

Simply reshaping complex AI / ML topics in terms of day-to-day action can remove barriers. Dr Sefus explained that one way to do this is to show that almost everyone has a mobile phone, and if you are talking to your phone or using face recognition to unlock it, or if you are getting recommendations for a movie or for the next song to listen to – All these are examples of interaction with machine learning. Not everyone understands this, especially non-professionals in technology, and showing people that these things are driven by AI / ML may be a revelation.

“Meet them where they are, show them how these technologies affect their daily lives, and have programming so that it’s very accessible – I think that’s what we need to focus on,” she said. .