I just learned that we built this very sophisticated artificial intelligence to deeply understand students technical competencies.
Which in and of itself didn't seem to be that predictive of anything.
So you need to know how to program to be a programmer. Sure. But it turns out that's not what predicts a great programmer.
Not having enough work. Climate change funding minus a high.
And. Large scale social disorder, antibiotic resistant diseases.
Education. Employment. Private capital for social good.
Quantum computing. Hello and welcome to the Feature Business podcast from say Business School.
I'm Emily Baron and each week I host a conversation on a topic that will define the future of business and wider society.
Speaking to experts from Oxford University, leading businesspeople and entrepreneurs,
I spoke to Dr. Vivienne Ming after her keynote at the annual Social Impact Careers Conference.
She's a theoretical neuroscientist and entrepreneur who describes herself as a professional, mad scientist and demented do gooder.
She's built applications for finding orphans in refugee camps and taking the bias out of hiring.
I started our conversation by asking her why she's an optimist about AI.
Well, I'm not an arbitrary optimist. I think we have some profound choices in front of ourselves as scientists, as business leaders, as policymakers.
And what I'm optimistic is that that we are not inevitably headed to something awful, but that we can make good choices and change the direction.
I am pessimistic in that right now most of the choices we make are not great, right?
But I'll explain what I mean. So I have been involved in a lot of different projects, broadly defined in the artificial intelligence space,
probably more accurately for any geeks listening to this in machine learning.
So way back when, when I was a full time academic,
we built computational neuroscience with theoretical neuroscience systems that learned how to hear or learned how to attend to the world.
We tried to understand how the brain works by starting from first principles like information
theory and then building machine learning systems that learned how to hear or see or attend.
And from that, we would discover all of these fascinating things about the world more in line with why than with what or how.
Why did we hear the way that we do? Why did we make choices the way we do?
And so it's a fun and amazing field of neuroscience.
And if it still seems abstract to you, just substitute the word theoretical with lazy.
I come from the field of lazy neuroscience where we don't actually have to run experiments.
So from there, I started to feel like there were insights that we could take out of that field to something higher, bigger.
One of the biggest insights in our field is brains respond differently to rich natural stimuli than they did to artificial lab stimuli.
Right. Well. If you think about education.
We have this rich learning environment, kids playing, spending time with parents, reading books, exploring the world.
And then we had an artificial lab where you give them a test.
And I thought, could we understand a child learning in the natural environment?
Mm hmm. Could that not just be the learning experience, but the assessment itself?
Right. Is them learning. And my wife, who happens to be herself a learning sciences researcher, we thought about this problem for a little while,
and then we thought about a potential solution, I guess you could say.
And we looked at each other and we thought, is this an experiment or is it a Start-Up?
And she had never done one. I certainly had not done a tech start-up before.
And it certainly was an education for me.
It turns out this is before Coursera and Khan Academy and raising money for educational technology was brutally difficult.
All the more difficult, if I may be so blunt, raising money as a woman.
And, you know, we we ended up exploring other potential markets,
but I quickly got tired with them because I realised I wasn't there to build a good business that would pay back my investors.
I was there to actually solve a problem.
So we immediately sold the company and we literally the next day we started an education company right in the same offices.
Except this time we didn't take any money. I funded it myself and we had two horses.
We actually we built and published some papers, built a system, did the research,
published papers showing that we in fact, we could listen to little kids in the classroom.
We could monitor college, university students and MBA students just chatting with each other online and do
better than the formal assessment and understanding what they knew or didn't know.
Wow. But more importantly.
We could do it at week three in the class rather than at the end of the class.
So as what is called a formative rather than a summative assessment, if we could tell you as the professor,
hey, these five kids are going to get this question wrong on your hypothetical final exam one.
Why waste time on the exam at all? And two, why not change?
Right now, what you're doing so that they don't fail.
So if I was going to I'd love to go back to that thing about the choices we're making and where we're making good choice in budget.
But just to dive into that very quickly. So I've seen a few education start-ups trying to do this in a very low tech way with pen and paper.
Has that approach been adopted anywhere in the States? I mean, certainly we're not doing formative assessment in Oxford University,
which is somewhere away from four from even even considering that a as form assessment.
But so there are many groups that are kind of working in this space.
And it's it is fairly transformative because this is what's called competency based education.
So the point isn't that you study for a fixed period of time and then you pass an exam.
It is you study until you understand the material. Right.
And then you're done. Right. And that it's even more different than that because it means now your job as a tutor, as a teacher, as a professor is.
Understand that student and what they need to be competent in the material.
So there are things like this going on in the world today.
But the funny thing is, along the way to building that system and publishing those papers,
I had a little detour as the chief scientist of this company called Guild, where we build A.I. driven systems to take bias out of the hiring process.
And you know what I didn't see amongst the literally hundreds of thousands of data points.
We looked at all the many, many variables we analysed.
The things that were not predictive of the highest quality work your grades, your test scores,
even the university you went to the most elite universities had positive but very modest in predictive validity.
In other words, a bachelor of Computer Science from Stanford was genuinely a positive predictor of someone's ability as a software developer,
but a pretty modest one. Whereas their motivation, Wright, correctly assessed, was a substantially bigger predictor, swamped it out.
So I jokingly tweeted One day at Carnegie Mellon is better than Berkeley and MIT is better than CMU,
and Caltech is better than M.I.T. and Stanford is better than Caltech.
And motivation is much bigger than any of them.
But we only hire. By looking at your name, your school and your last job.
That's the starting point for every hiring process at almost any company.
So think about what that means for my work in education.
I just learned that we built this very sophisticated artificial intelligence to deeply understand students technical competencies.
Which in and of itself didn't seem to be that predictive of anything.
So you need to know how to program to be a programmer. Sure. But it turns out that's not what predicts a great programmer.
Interestingly enough, as a small aside, we find that social skills, though less common in programmers than, say, salespeople, are just as predictive.
Right. Which, by the way, goes against a somewhat notorious former Google Engineer's claims about software engineers.
So we really wanted to rethink them what education actually means.
And this was much of a why, why, why process for us.
Why do we have a formal education system globally?
In America, the Western world, whatever you want, however you want to look at it.
And to me, it's, I hope, obvious that it's not about producing good grades or high marks.
It's not about going to university. It's not even about getting a great job.
Though any of those might well be mediators of what I really care about.
The purpose of education is to produce happy, healthy, impactful lives and let society reap the benefits.
And in that case, it means anything we might do in education is only valid if it supports that,
and it's only valid if it supports that for this child.
That gives you a pretty wild ambition then.
Educate people based on a predictive model of how it will impact their long term life outcomes.
And so that's what we did now, because we knew it would work, because we even know it will work.
Today, though, I think we've done enough research and real world application and now a couple of years of
actually being live in the world where we can see it sure looks like it's having an impact.
So we revisited education and we thought, well, who owns the longest term outcomes for a child?
And it's their parents and other caregivers, grandparents, foster parents, whoever it might be.
So what if we built a tool to help parents?
And in supplying that tool, it gave them activities that they could do with their kids.
Like, how about something you can do with your kid tonight?
Do you have 20 minutes? What's the single thing you could do with your child that would have the biggest impact on their long term outcomes?
So I do want to jump in there because he says I'm out of this one, which I thought was fascinating.
You mentioned the growth mindset, which has been, you know,
so important for lots of educators understanding of how to do the best by the kids they're looking after.
And you said the biggest predictor is the parental growth mindset, which I thought was a really kind of cool phrase.
So when you have these predictive models which can tell you, you know, if you are X,
Y, Z stage when you were 11, we know what's going to happen when you're 25.
How do you balance the power in that knowledge with giving parents the right tools at the right time,
but not to the extent that you can, you know, give them a preconceived notion of what that kid's going to achieve.
And you can most certainly lead them down the wrong path.
So when I say predictive models, this is the language of my field.
And in all fairness, I think can often get misinterpreted,
like perfect crystal ball predictions of the future, none of which is a reality in our work.
The simple idea probably an easier the less engaging way described as they're actuarial models.
Right. And what we're trying to do is say, if we look at enough of different factors at a given moment in a kid's life.
What could we do with the highest confidence to have and minimise any potential downsides?
And add. Whatever.
I'm going to make up a magical thing, a life outcome score.
What if it was 20% higher? Right. We're not talking about maxing out everyone.
I can't do that. I gosh, I wish I could, but can I make a positive difference?
Right. And it turns out the one not easiest thing I can do, but the one most obvious thing I can do.
The thing that parents would many parents would love to have is the exact worst thing to do,
which is tell them who their child is or who you predict they will be.
And as soon as you tell them that it's a cursed crystal ball and you just made everything worse.
Even if your predictions are positive, hey, your child's going to win the Nobel Prize.
I just made it less likely to happen now.
It will it will actually decrease your growth mindset about your child because now you're worried, oh, god, I don't want them to not do this.
And you become more fragile and more brittle in your approach. How do we focus on the things that will make a long term positive difference?
Some of these are phenomenally reliable literacy interventions are universally good resiliency interventions,
appropriately applied growth mindset interventions.
Yes, it is possible to run a resiliency intervention where you set the bar so hard that the kid just fails and all they learn is failure.
And you don't get anywhere, but you do it right.
And these things, you know, I was once interviewed for the BBC and the interviewer was like, You can't know what people will need in 20 years.
How could you possibly say that? And I say you're right.
You know, if you asked me, does any of my empirical research show that kids will need to be resilient in 20 years?
Well, I don't happen to own a TARDIS, so no, I haven't been in the future.
And so I don't know. But if you can imagine a world where being resilient isn't helpful, then you have an imagination.
I do not. It is such a ubiquitous predictor of positive life outcomes today, and for such obvious and intuitive reasons,
though we can study it more deeply than that, that it's fundamental.
So we do find there are other things that are more nuanced,
and our goal is to own the responsibility of making certain that the sorts of things we recommend are safe, reliable and will make a difference.
So there are things that, particularly with older children, where they become a little more differentiated, right?
One child may be very resilient emotionally, and so getting tough feedback works perfectly well for them, but not everybody is.
And one of the things we focus on is not simply absolutely don't tell this parent, here's your child and here's how they compare to everyone else.
That's awful, and here's who they will be is just as bad.
Here's who they could be, is what we want to communicate.
But even internally in our system, when we measure all these different constructs that we look at.
When we focus on delivering an activity to a parent, it's not because this child has a strength in that, and we're we're augmenting it.
It's not that the child has a weakness and we're remediating it.
What we actually look at, again, for you nerds and geeks is the gradient on that vector.
We want to know where they're changing. Where does this child the most plastic?
No one's really done this research before. So we're kind of naive.
Is working on a strength better than helping a weakness? It's not entirely clear.
So what we figured is at any given moment, so as far as we can tell,
everyone's plastic in some part of themselves and certainly relative to other things about them.
Focus on that thing. Yeah. Or maybe those few things.
So, you know, the concern that you're articulating, which is you could get a wrong you could mislead the press,
all of that is is very reasonable and not more than reasonable.
We are obligated to take all of that deeply, seriously, and we build it into the models.
Right. It doesn't mean that it's perfect, but the whole thing is a grand experiment and we learn and literally iterate on a daily basis.
So one of the things I wanted to pick up on there and sort of just as an aside, one of the kids I sort of knew in my previous life before the MBA.
I remember him saying to someone, this kid from a, you know, just French background and says He London.
And I remember saying that his his life ambition was to be a labourer because
the richest person he knew was someone who earned $2,000 a month and had a dog.
And for him, in his worldview, that was, you know, the kind of that that was that was it.
And one of the things you said earlier, which really struck a chord with me, was the phrase your belief based utility.
And I'd love to understand from you whether there's any work you're doing now to use these kind of tools, trying to help people who don't have that.
Very much so. It's one of the constructs very explicitly.
It's that as an idea is a fairly new one out of behavioural economics.
So we've sort of adopted the language in the knowledge base of people like George Loewenstein and others that have done research in this space.
It was something that I had intuitions around even before then, and we were working in several years ago, maybe five years ago.
I read this paper and it described a pretty well-known phenomenon in the States and a variant of it that exists everywhere in the world.
Students from underrepresented backgrounds, but high performers, you know,
elite students in secondary school get full scholarships to go to Harvard, go to Stanford.
And to say they do it and they turn down those scholarships at rates higher than a traditional student sort of read.
White male is. I mean, the traditional students don't turn down these scholarships, but for peculiar reasons.
So it's, it's almost a totally different behaviour, but they do it and at fairly high rates.
And for a hundred years armchair philosophers in America have said, well, you know,
black families are different, they're culturally Hispanic families, it's the economics.
Finally, a few years ago, someone did just what seems like the most obvious experiment.
Some of them go and some of them don't. What's different between them?
And it turned out there was nothing different between them systematically in terms of culture and economics.
And in fact, of the dozens of variables they looked at, only three were meaningfully predictive and the number one far and away.
They knew someone from their neighbourhood that had gone before them. Right.
And you know, the way I just told the story in terms of race and probably is how many people were interpreting it even before I brought that up.
But as I began to think about this, I realised this was my dad, right?
He grew up in a farm in the south central part of Kansas.
Mm hmm. And I mean a tiny farm.
Like, if you wanted to go visit the town that he grew up in, you have to push the tumbleweeds out of the way.
And in after three years of secondary school, he had already graduated.
He got a full five year non-performance based scholarship to MIT, and he didn't go.
And the reason he didn't go, admittedly a little less about him than about his grandma, my grandparents, his parents.
What's the point of going to MIT? If you're just going to end up back on the farm, right.
In yes. To me, one single generation later, it seems irrational.
Yeah. What? What could your life be if he had gone off and there was its own pressure on me to then,
you know, try and be this kid to be the one that kind of lives out the dreams that he had had.
I mean, his life was not ruined. Ended up becoming a doctor. I grew up in California.
You know, it was it was an amazing experience.
But he always felt that he hadn't. He always described himself as, you know, some small town doctor.
And it was clear he always thought he could have done more than that.
And he made it very clear to me to live a life of substance that that really had an impact on the world.
And he built that even when I went through very hard times in my life.
And that was something he built deeply into me.
So when I came out to the other end, that was still there. So you see, this is a really broad based thing.
I'm willing to bet in the UK there's probably a very strong North-South gradient where equally performing students,
equitably performing students from the north are less likely to attend elite universities,
even on invitation than those from further south, perhaps with an interesting border effect.
And and, you know, that's a tragedy if you look at the work of people like Raj Chetty, an economist at Stanford,
he had this set of papers about a few months ago that got a lot of press about lost Einsteins.
Mm hmm. He found, for example, that a student from the lowest economic quintile.
But the top math performance quintile.
Yeah. Was as likely to have a patent in their life as a student from the top economic quintile.
And the lowest math. Wow. And that means we all have lost.
And of course, when you talk about tears, you look at how many of those kids you're talking about.
It is profound. It is self-destructive that we perpetuates these sort of things.
So, yeah, when you look at belief based utility and you say, what do I think is really going to pay off in my life?
What do I think is plausible? It's possible. Role models are huge impact.
They're not the only factor, but they are huge impact.
Peer Remodelling Parent Role Model. Turns out role modelling by elite performers less so.
You know, the idea that there was a guy who was the president and his dad was from Kenya is not necessarily very motivating to a kid.
You know, growing up on the streets whose family has lived in the rough part of any number of cities
around America for a long time and and has experienced discrimination his whole life.
It's easy to look at President Obama and say he's an outlier or even someone that came seemingly from a similar background like Oprah Winfrey.
You still look at her and you say, sure, she's a billionaire because she's exceptional and it's hard to believe that could be you.
One needs that personal connection.
So a big part of our work is how can we actually help to engineer some of these experiences, both the personal experiences,
but also an engineer that I'm kind of at an epidemiological like if we can go in and create some of these differentials,
as we call them, lift experiences even, it's for it's for a substantial minority of the kids in these neighbourhoods.
Then they become the kid that all the ones around them know.
They become the one from the neighbourhood that came to Oxford or if they had to slam Cambridge.
Hampshire is acceptable the son. And so looking at that and thinking we could actually make a difference is a huge motivator in this.
And it's not as much as I might want it to be.
It's just never going to be in their term. How do we change 8 billion lives?
That may be our ambition.
But realistically speaking, there are hundreds of millions, even potentially billions of lives that are within the scope of what we can change.
And this very simple idea. I mean, it is such a subtle one, not simply that anyone can be amazing.
It's sort of an ethos of Silicon Valley. Anyone can be amazing.
But if you're not, it's not my fault, right? We hire the amazing people. Everyone can be amazing if that's true and someone isn't.
You own them. You don't own all of it. I'm not saying you're a bad person because you're drinking a latte walking past a homeless person,
but you do own some of the moral responsibility to try to make a difference in the lives around you.
Because it's in your self-interest to do so. Right.
So this has been a big part of I just happen to deal with numbers.
I happen to work with algorithms and and entrepreneurship and brains and these sorts of things.
But ultimately, it's a very human story. Thank you for listening to this episode of the Feature Business Podcast.
Next time I'll be talking to Courts of Paris and MBA student and expert on climate change.
We discuss two degree warming and the impending carbon bubble.
Please do subscribe to this podcast in iTunes or wherever you get your podcasts.
This episode was brought to you by Paris, Michael and Brady.
Patrick and Emily, thank you very much for listening and goodbye, all.