This is a fascinating conversation between Fei Fei Li, a computer science professor at Stanford and co-director of their new Human Centered AI Institute, and Yuval Noah Hariri, a historian and author of the widely popular book Sapiens. The two have a respectful go at one another on what the future looks in an AI world.
Machine learning is much better at doing certain things than people, just as a dog is much better at finding drugs than people, but you wouldn’t convict someone on a dog’s evidence. And dogs are much more intelligent than any machine learning.
The problem with this statement is that we have convicted people on a dog’s evidence and later found that evidence to be faulty.
Outside of this issue, Benedict Evans provides a simple definition of artificial intelligence bias, scenarios of the potential bad effects of AI bias, and how we can mitigate those effects. Evans’ central point is a good one to keep in mind:
ML finds patterns in data – what patterns depends on the data, and the data is up to us, and what we do with it is up to us.
This is an interesting partnership probably arising from both startups being Y-Combinator alums. Paystack has gotten quite a lot of traction in Nigeria providing a payment platform similar to Stripe. Lambda provides software development training free of charge until folks get a job making at least $50k. After this, they’ll have to pay 17% of their salary for tuition over two years.
I’ve seen a lot of VCs pointing to Lambda as the chosen one to lead us into a new model for education based on this model. First – their not the only education business doing this, African Leadership University uses a similar model. Second, I worry that folks could still find themselves stuck with collectors hands in their pockets. I’d be curious to see what the income threshold will be for this Paystack partnership.
Russia’s State Atomic Energy Corporation has been aggressive about pushing nuclear development across Africa. Over the past five years, the company has been at various stages of talks with South Africa, Kenya, Zambia, and Ethiopia. It’ll be at least a decade before we see how all this plays out but it’s quite interesting.
This is a strong quote from Yewande Sadiku, head of Nigeria’s Investment Promotion Commission, at a recent event honoring the late Professor Michael Ayo Ajomo:
“it is true that Nigeria has challenges, but when we are going into a negotiation that is not the toga that we wear, the toga that we wear is the toga of a country that is the 26th largest economy in the world and is estimated by 2050 to be the 14th largest; the toga of a country that is the 7th most populous country in the world and is estimated that by 2050 would become the 3rd most populous country.”
I don’t know anything about Professor Ajomo and look forward to learning about him. As for the quote, direct investment in the country during the Buhari administration peaked at nearly $4.5B in 2017. It will be interesting to see how investment in the country shifts once the refinery Dangote Industries is developing comes online in 2020. Dangote expects the refinery to meet all local demand and position the country to export finished oil products. This could change things for how oil investors think about the competitive landscape in the country moving forward.
I have been a Twitter user since February 2009. The platform has played a key role in expanding my world view and connecting me to now friends and mentors. It’s played a key role globally shaping the relationship between citizens and their governments.
The platform has also been quite harmful. The levels to which folks face harassment on the platform is quite alarming. For those who have been on the receiving end of that harassment – terrifying, I have to believe.
I’ve watched and listened to numerous interviews Jack Dorsey has given over the past couple years and there seems to be this disconnect in how quickly he plans to address the issue. Apparently, this was the case during his TED interview yesterday. I look forward to watching the video once it comes out.
This is a good interview with Andrew Ng, one of the foremost experts on the development of artificial intelligence from an operator and academic perspective. He makes the case here for folks to layer their expertise in various disciplines with an understanding of AI considering the impacts the technology is having across industries.
Ng also makes the case for conditional basic income rather than universal basic income for fear that folks will get trapped in certain jobs, namely gig economy jobs. I share this concern.
The one thing that frustrates me in conversations with AI experts is their positioning of certain AI developments being so far down the road that we shouldn’t spend a lot of time worrying about them. I worry how that gives space for the development of bad habits in AI technology that lead us to points of regret along this path we’re on.
I’ve spent the past week crafting words about this memo. After a fantastic meeting earlier today, I’ll just speak plainly. For us to have the responsible capitalism Howard Marks calls for in this piece, we have got to get to the point where we have a frank conversation about how the U.S. economic pie got so massive and how we’re in a place where it divvies up so unequally.
Our modern capitalistic society didn’t emerge from a vacuum. The foundations that set the stage for this thing trace back the beginning of this country. Over the course of history, slavery, the rollback of Reconstruction, redlining, and more messed with what the invisible hand of the market should have handled as the smartest, most talented, and hardest working folks competed for their share of the pie. We are where are today, but you can’t point to the faults of the populist left’s resentment towards capitalism without doing a thorough examination of why that could be. We won’t get responsible capitalism that way.
Nearly 900 million people are eligible to vote in India’s elections which began last week and outpace several of the largest democracies in the world combined. In order to manage the scale of the elections and ensure their success, today is the first of seven election days that will that will wrap up next month.
While tedious, the approach might have been helpful to Nigeria’s elections during which voters had to endure a last minute call to delay the vote. With the mix of the country’s size and security challenges in some areas, perhaps breaking the election up into easier digestible pieces may have helped.
I’m curious to see what turnout looks like for India’s elections in comparison to Nigeria’s shockingly low one.
The most important part of Amazon’s shareholders letter in my opinion is the following section:
We’re also plunging into helping companies harness Machine Learning. We’ve been working on this for a long time, and, as with other important advances, our initial attempts to externalize some of our early internal Machine Learning tools were failures. It took years of wandering – experimentation, iteration, and refinement, as well as valuable insights from our customers – to enable us to find SageMaker, which launched just 18 months ago. SageMaker removes the heavy lifting, complexity, and guesswork from each step of the machine learning process – democratizing AI. Today, thousands of customers are building machine learning models on top of AWS with SageMaker. We continue to enhance the service, including by adding new reinforcement learning capabilities. Reinforcement learning has a steep learning curve and many moving parts, which has largely put it out of reach of all but the most well-funded and technical organizations, until now. None of this would be possible without a culture of curiosity and a willingness to try totally new things on behalf of customers. And customers are responding to our customer-centric wandering and listening – AWS is now a $30 billion annual run rate business and growing fast.
Amazon has turned different parts of its business inside out in order to remove bottlenecks and get assists from customers in accelerating the development of its technology. Jeff Bezos points out the results of that in the first section of the letter – third-party sales have gone from $0.1 billion to $160 billion between 1999 and 2018. None of us can fully appreciate that. Now, layer the exponential power of AI on top of Amazon’s ability to build a country from nothing, and go sit in a corner with a Tastykake and RC Cola as Coach Merritt used to say. Twenty years from now, we’ll be using Amazon One-Thought to order items and six years away from knowing whether Ray Kurzweil was right about artificial intelligence hitting go-mode. What a time to be alive. Are we ready?
Africa is projected to have more people at working age than the rest of the world’s population by 2035.
By 2045, artificial intelligence is projected to reach the singularity, where it will be self-improving rapidly rather than being dependent on human inputs.
On their own, these two developments are concerning. For years now, policymakers have braced themselves for what could happen once there’s this critical mass of working age folks in countries like Nigeria and South Africa with no jobs. I’ve heard the term “tinder box” more than I care to.
Artificial intelligence learning on its own is something very hard to envision unless you want to leave that to your pick of scariest movie about AI. All of the advances we see in AI currently are still in the realm of supervised learning where humans input enormous amounts of data. Yet, AI is already able to some pretty incredible things. My Google Home is in constant use in my home for music, information, games, story time, and more.
What happens at the intersection of these two shifts? They’re supposed to happen within a decade of each other. Are African policymakers thinking about curriculum that could prepare their populations to be able to work alongside a robot?
For example, Rwanda, Kenya, and South Africa are investing a lot in growing their automotive manufacturing industries. The price of industrial robots is dropping rapidly and could make the development of those industries a lot more realistic. Just this year, Volkswagen and Nissan have launched assembly plants in Rwanda and Kenya respectively. Are the workers at these plants ready for an increased use of robots?
If you’ve seen examples of analysts and policymakers thinking through this issue, I’d appreciate you sending that info my way!
3. Sometimes, these assurances that we have nothing to worry about when it comes to artificial intelligence feels like my back is being rubbed with the flat side of a freshly sharpened sword. (via Marc Andreessen)
5. The controversy surrounding Justin Gatlin being the fastest person in the world after serving two doping bans frustrates me. He paid his dues, yet people continue to demonize him. (via Track and Field News)