Byron speaks with Didem Un Ates, the Senior Director of AI customer and partner engagement for Microsoft about Artificial Intelligence.
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Following her Electrical Engineering and Management studies at the University of Pennsylvania, Didem started her career with management consulting at CapGemini and Motorola. After graduating from Columbia Business School (CBS) in 2005, Didem continued her career at Greenwich Consulting (now part of EY) and British Telecom in London, UK.
Her passion for technology led her to join Microsoft’s Information & Content Experiences Group where she and her team signed c. 1,500 partnerships across 60 markets. She held other business development and partner management roles as part of Microsoft Accelerators and the Business AI teams. In her current role, Didem is focusing on scaling Microsoft’s SaaS AI solutions such as Dynamics Customer Service Insights and Virtual Agent.
Didem has 20+ years of multinational leadership experience in business development, management consulting, and product management in executing international rollouts, implementing new market entries, and building new revenue streams from disruptive technologies in EMEA, APAC, and LatAm.
Byron Reese: This is Voices in AI brought to you by GigaOm. I’m Byron Reese. Today, my guest is Didem Un Ates. She is with Microsoft and her title is the Senior Director of AI Customer and Partner Engagement. She’s been there for several years. She holds two degrees, including in electrical engineering, from the University of Pennsylvania and she has an MBA from Columbia as well. She’s joining us from London. Welcome, to the show, Didem!
Didem Un Ates: Hi, Byron. Thanks for having me.
I always like to start with the same group of questions, which begins with: What is artificial intelligence and why exactly is it artificial? What’s artificial about it and what is intelligence for that matter?
Thank you. The way I try to explain it to my customers, partners and other individuals like students at schools – universities or high schools, is basically: artificial intelligence is a way of mimicking our brain. Intelligence makes sense of things around us. It’s how we process our environment, how we make sense of it, make these connections between the past and the future and the present, that’s called general intelligence. Then we also have specific intelligences, which is all very specific functions like object recognition or speech recognition. ‘Artificial’ is trying to mimic this with technology, with algorithms.
Well, it’s interesting you’re saying the word ‘mimic.’ Is that to imply it’s not actual intelligence? It’s just doing something that can emulate intelligence or do you actually think it’s smart?
No, it’s definitely smart and it’s – in some cases, the specific intelligence that I referred to, some call it weak AI, is actually already smarter than humans in those areas. Microsoft actually was the first to surpass human intelligence in speech recognition, translation, object recognition etc. Yes, some of these functional areas are already very smart and even smarter than humans, but the general AI, or the strong AI as some like to call it, is around a five year old’s intelligence level. That’s why I call it ‘mimic.’
When you say – you think we’re at a five year old [level] for general intelligence, is that really the case? It seems to me that we have this one trick that’s been working pretty well for a while, which is machine-learning, where we take a bunch of data about the past and we study it and we make projections into the future. That seems to be a really – not a very generalized tool. There are a lot of things where the future’s not like the past. The word ‘banana’ is said the same way tomorrow and yesterday so it’s a really good thing that you could do that.
Things like creativity and other sorts of things we associate with general intelligence, are they even solvable that way? When you say we’re at a five year old, that means maybe next year we’ll be at a six year old, at a seven, and then in 15 or 20 years, we’ll be at a teenager. Is there a limit to our one little trick we know here and what it’s going to be able to do?
These are great questions, and I think similar to you, Byron, I’m obsessively reading about AI and trying to get different perspectives on the experts, mostly at the universities but also the industry. To me, when I say – or when we read about the general intelligence is around the age of a five year old human being right now, all it means is as we improve the algorithms around AI and ML, we mimic the human learning – human brain and it is at the level of a five year old human being. Some of course predict actually that general AI are actually racing to reach an adult human mind. It’s my personal view, not Microsoft’s view by far, but my personal view is: yes, AI/ML will reach adult intelligence, but when this will happen is a big question.
To your point about teenager years, some predict that it will be happening in five years; others are saying it won’t happen in a century. The average at least in my reading and research is somewhere around 15 to 25 years. This is completely my own – let’s say doing my own homework. This is quite serious because it has many implications in terms of let’s say, automation or impact on society, jobs, changes, exciting things coming, and also lots of integrations that we should proactively manage in terms of responsible ethical AI, which we are, as Microsoft, very, very, serious about. Does that answer your question?
I don’t know if you can say there’s a group of people who think we’re going to get it very quickly and then there’s a group of people who think... Andrew Ng is worrying about over-population on Mars, centuries and then you can somehow average those. People who think it’s going to happen quickly or people who think intelligence is fundamentally very simple and it’s a few tricks and that we’re going to figure it out and have it very quickly. I think it boils down to a bigger question. Let me just put my bigger question to you, which is: Do you believe that people are machines?
That’s a great question. Yeah, I actually think today and in the history of the human race, actually yes, we have been machines, sadly. When I say machines, we have had to do some tests that actually made us like robots.
No, I agree with that part: Using a person to dig a ditch or something, but I mean something even more fundamental. Do you believe anything happens in the human brain that can’t be explained by physics and electricity and chemistry?
Is your brain an actual piece of machinery that can be emulated or are you not a machine? That maybe you have –
Again, my personal view is conscience cannot be replicated by machinery, or some call it spirit or whatever, so that part is very different. Other than that, I personally think that, yes, our bodies are machines, so as long as we fix the problems with our bodies, we could actually live very long lives. That holds true for the brain as well.
That part of the brain that is consciousness, that part of the brain that experiences the world, that part of the brain which may be spiritual or what have you, that may be where our special intelligence comes from. That may be where we get all this stuff we are able to do that seemingly grasshoppers can’t do, and maybe it comes from those things. If it does come from those things, that means we’ll never make it, because if your brain isn’t a machine –
Yes, yes, I’m with you. If you’re believing in consciousness and spirit and this overarching universal intelligence, I agree with you. I actually studied electrical engineering as well so I tend to think very analytically. So when I refer to: yes, we can replicate the human body and brain, I’m referring to the mechanical parts of course; I’m not referring to – if you’re calling that consciousness as applicable.
You do a lot of activism and you’re very passionate about certain topics in artificial intelligence. Can you talk a little bit about those, about what you do and what the message is that you would like the listeners to hear?
Thank you so much, yes, absolutely. I am very, very passionate about technology and especially disruptive technology. My whole career is about scaling disruptive technology in a meaningful way so that people can live better through technology. I have been involved, actively, in the AI space in the last three, four years and in parallel actually before AI as well, I have always been very passionate about diversity, inclusion, and stem; encouraging females, minorities and under-represented groups to embrace technology. They could be dancers, they could be artists, it doesn’t mean they have to study computer science or engineering. Embrace the technology to live better and to do whatever career or passion they choose to pursue. I have always been passionate about that.
In the recent years, as I was saying, last three, four years, as I work with AI, which is fascinating - there is so many things we could expand on there - I also started to feel very responsible about the implementation, the scaling of this technology. The most practical and impactful way has been to host hackathons and bootcamps. We started off with females because they obviously represent just 50% of the population worldwide, but it can be done with minorities and other groups. They’re called ‘Girls in AI’ bootcamps and hackathons. We piloted a few in Europe as well as US and they have been immensely helpful.
My message here is as some of your audience will know: the current split of AI/ML talent is only 12% female and it’s declining. This is a terrifying statistic. Why? For three reasons. First one: products are being developed by the majority for the majority and however kind intentions they may have, the diverse perspectives that are needed for these complex solutions isn’t there, so 88% is very dominant. The second reason concerned with this is: data is biased. Again, data is heavily male-oriented or majority oriented, which of course is a big challenge in implementing AI solutions. The third challenge is job automation impacting female jobs the worst. We see this – one very tangible example I believe is cashiers. Currently, in the US, 73% of cashiers are women and 97% of cashiers are expected to lose their jobs to automation.
While AI and ML will bring many exciting jobs and make our jobs much more meaningful, they will also replace some jobs, so these replacements are going to hit the minorities the hardest. I feel very responsible to change this trend, and I would encourage all your listeners, all our audience, to think about how they can, as individuals or as organizations, actually try to help reverse this trend for everyone’s benefit.
What are some suggestions along those lines that you have?
First of all, the easiest free and super easy thing to do is share some reliable AI and ML learning resources. These can be simple eBooks - Microsoft has plenty of these - or they could be online learning courses. I’m pursuing a degree in AI on edX, a Microsoft professional degree for AI, which is free of charge. Or it could be AI Labs. We have Microsoft AI Business School, Microsoft AI Labs, where you can just, free of charge, go there, train yourself as a student, as a business leader or a technical talent.
The second thing, in addition to upskilling ourselves and our environment, sharing these resources, is getting hands-on experience with bootcamps and hackathons. This is the way technology works. We have to get our hands dirty. In other words, you could come up with a project, it could be a personal passion, it could be a disability that you want to actually fix. For example, one of our blind engineers in the UK came up with an app called Seeing AI, which allows blind people, as well as seeing disability – people with seeing disabilities like old people, help see their environment. This is a fantastic example of how we can get our hands dirty and implement AI in any shape or form.
I think the third thing is that it’s actually educating the next generation. Whatever school they are going to, whatever fantastic education they may follow, I’m afraid the education system isn’t up to date to include the upcoming changes. No one knows what the jobs will be in five, ten years, so whatever our kids are studying, actually will be irrelevant in a way in terms of jobs and careers. That’s another area that I would recommend experts to focus on, and the public.
You made the comment that AI is going to disproportionately affect women-dominated jobs. I’m just trying to think that through. Is that really the case because when you stop and think about it, the number one job you hear about being automated is truck driver and those are virtually all men, and then taxicab drivers, that’s male-dominated, then delivery drivers are predominantly men. Has that been studied, the make-up of –
I can definitely share a few studies. The statistic that I got about cashiers for example, came from a WIRED and Element AI study. I’m with you; it’s not that important whether the top – the jobs that are at highest risk of automation will hit the females or minorities worst. One of the impacts of the technologies, as I said, there’s data bias, there’s product development challenge and job automation. I didn’t mention the top jobs at risk will be female jobs. What I’m mentioning is there are some specific sectors that are heavily female and unfortunately, it looks like those will be impacted quite heavily. What I’m saying is females, or minorities, will be even more marginalized than in the past, if we don’t act and reverse this trend.
Fair enough. Now, Mark Cuban, I read an interview with him and he said the first trillionaires are going to be from AI and I thought, yeah, yeah, I believe that. You're talking about a technology that allows you to impact everybody in a major way and that’s probably true. That’s a person who really gets it. Then I saw another interview where he said, if he were coming up today, as a student, he wouldn’t study STEM; he would major in philosophy. I wonder what you think about that.
I love it!
– but what he says is, you’ve got to understand the world and all of these other things. If we just corral everybody into STEM, I don’t know that we’re serving the future well. What do you think?
I love it. To me, when – as part of my social impact and charity work, I do work hard to encourage minorities to embrace STEM and so on, but in my mind, actually in a few years, in the very short-term future, we won’t need coding skills. All of that will be very easily done for us. It will be simplified, let’s say, unless you really want to dig very deep and do your PhD and do other stuff. In philosophy, ethics, they will be very, very important areas to go deep on, I completely agree.
Having said that, forget even the majority of the society worldwide. When I have my conversations with my customers and partners who are in technology space, it does become quickly apparent that we, including myself, aren’t as well educated, trained about AI and all these technologies as I think we should be. Why? Look at all these scandals with privacy and user engagement on social media companies, all these things stem from the fact that even the players in this sector are not well equipped to manage the risks.
There are so many cases, I don’t need to go into the detail but for me, STEM has to be the baseline or embracing the technology let’s say. You don’t have to study science or computer science, but embracing the technology is a given, just like food and water, basically. On top of that, going deep on philosophy or ethics or how do you scale these technologies responsibly is absolutely critical.
Well, it seems we’re coming up on time here. We could talk for a long time. I applaud you for the work you’re doing. If people want to keep up with you and all the things you’re doing in the world, what are some of the ways to do that?
First of all, in terms of diversity, inclusion, STEM, encouraging anybody, helping anybody in terms of embracing disruptive technologies now, it’s these AI/ML but who knows what it will be in the next few years, it could be autonomous systems. I’m always available on LinkedIn, Twitter. I’m very, very happy to help mentor or coach people around this. It’s a passion of mine. If it’s a business inquiry, obviously they should specify that and I’m very happy to help in any way I can; that’s my job.
Well, you’re a fascinating person and for people who want to keep up with you, follow you on social media, how do they do that?
Thank you so much, Byron. I’m on almost everywhere. My Twitter handle is @didem_un_ates and I’m at LinkedIn as Didem Un Ates. Thank you so much.
All right, well, thank you so much for your time. Would love to have you back again.
Thank you, Byron, it’s been a pleasure.