Here are my notes from The Future of Intelligence, a Conversation with Max Tegmark on the Sam Harris Podcast.
You can listen to it here:
My notes and thoughts:
- We always focus on the downsides of super intelligent AI. There are, however, upsides. Super intelligence can help solve some of the biggest problems of our time: Safety, medical issues, justice, etc.
- Containment is both a technical and a moral issue. Much more difficult than currently given credit for. Given ways we have to construct it, we likely can just “unplug” it.
- Tegmark defines these three stages of life:
- Life 1.0: Both hardware and software determined by evolution. (Flagella)
- Life 2.0: Hardware determined by evolution, software can be learned (Humans)
- Life 3.0: Both hardware and software can be changed at will. (AI machines)
- Wide vs narrow intelligence: Humans have wide intelligence. Generally good a lot a lot of different tasks and can learn a lot implicitly. Computers have (so far) with narrow intelligence. They can calculate and do programmed tasks much better than us. But will completely fail at needing to account for unwritten constraints when someone says, “take me to the airport as fast as possible.”
- The moment the top narrow intelligence gets knit together and meets the minimum of general intelligence, it will likely surpass human intelligence.
- What makes us intelligent is the pattern in which the hardware is arranged. Not the building blocks themselves.
- The software isn’t aware of the hardware. Our bodies are completely different from when we were young, but we feel like the same person.
- The question of consciousness is key. A subjective experience depends on it.
- We probably already have the hardware to get human-level general intelligence. What we are missing is the software. It is unlikely to be the same architecture as the human brain, likely similar. (Planes are much more simple than birds.)
- AI Safety research needs to go hand-in-hand with AI research. How do we make computers unhackable? How do we contain it in development? How do we ensure system stability?
- One further issue you are going to need to overcome is having computers answer how a decision was made in an understandable way instead of just dumping a stack trace.
- Tegmark councils his own kids to go into fields that computers are bad at. Fields where people pay a premium for them to be done by Humans.
If you write any sort of code or markup in iOS 11, constantly getting curly quotes out of your keyboard will drive you crazy.
The feature is called Smart Punctuation and here is how to turn it off:
Go to Settings > General > Keyboard. Toggle off Smart Punctuation.
I’m working my way through Rolf Dobelli’s The Art of Thinking Clearly by reading a few sections each morning. Below are my notes on sections 12-23. Read 1-11 here.
- “It’ll-get-worse-before-it-gets-better” fallacy: A variant of confirmation bias. If the problem gets worse, the prediction is confirmed. If the situation improves unexpectedly, the customer is happy and the expert attributes it to his prowess. Look for verifiable cause-and-effect evidence instead.
- Story bias: We tend to interpret things with meaning, especially things that seem connected. Stories are more interesting than details. Our lives are mostly series of unconnected, unplanned events and experiences. Looking at these ex post facto and making up an overarching narrative is disingenuous. The problem with stories is that they give us a false sense of understanding, which leads us to take bigger risks and urges us to take a stroll on thin ice. Whenever you hear a story, ask: Who is the sender, what are his intentions, and what does this story leave out or gloss over?
- Hindsight bias: Possibly a variant on story bias. In retrospect, everything seems clear and inevitable. It makes us think we are better predictors than we actually are, causing us to be arrogant about our knowledge and take too much risk. To combat this, read diaries, listen to oral histories, and read news stories from the time you are looking at. Check out predictions from the time. And keep your own journal with your own predictions about your life, career, and current events. Compare them later to what happened to see how poor of a predictor we all are.
- Overconfidence effect: We systematically overestimate and our ability to predict on a massive scale. The difference between what we know and what we think we know is huge. Be aware that you tend to overestimate your knowledge. Be skeptical of predictions, especially from so-called experts. With all plans, favor the pessimistic scenario.
- Chauffeur Knowledge: There are two types of knowledge: Real knowledge (deep, nuanced understanding) and Chauffeur knowledge (enough knowledge to put on a show, but understanding to answer questions or make connections). Distinguishing between the two is difficult if you don’t understand the topics yourself. One method is the circle of competence. True experts understand the limits of their competence: The perimeter of what they do and do not know. They are more likely to say “I don’t know.” The chauffeurs are unlikely to do this.
- Illusion of Control: Similar to placebo effect. The tendency to believe that we can influence something over which we have absolutely no sway. Sports, gambling, etc. Also: Elevators, cross walks, fake temperature dials. This illusion led prisoners (like Frankel, Solzhenitsyn, etc) to not give up hope in concentration camps. Federal reserve’s federal funds rate is probably a fake dial, too. The world is mostly an uncontrollable system at the level we currently understand it. The things we can influence are very few.
- Incentive Super-Response Tendency: People respond to incentives by doing whatever is in their best interest. Extreme examples: Hanoi rats being bred, Dead Sea scrolls being torn apart. Good incentive systems take into account both intent and reward. Poor incentive systems often overlook and even corrupt the underlying aim. “Never ask a barber if you need a haircut.” Try to ascertain what actions are incentivized in any situation.
- Regression to Mean: A cousin of the “It’ll-get-worse-before-it-gets-better” and the Illusion of Control fallacies. Extreme performances are often interspersed with less extreme ones. There are natural variations in performance. Students are rarely always high or low performers. They cluster around the mean. Thinking we can influence these high and low performers is an illusion of control.
- Outcome Bias: We tend to evaluate decisions based on the result rather than the decision process. This is a variant on the Hindsight Bias. Only in retrospect do signals seem clear. When samples are too small, the results are meaningless. A bad result does not necessary indicate a bad decision and vice versa. Focus on the reasons behind actions: Were they rational and understandable?
- Paradox of Choice: A large selection leads to inner paralysis and also poorer decisions. Think about what you want before inspecting existing offers. Write down the criteria and stick to them rigidly. There are never perfect decisions. Learn to love a good choice.
- Liking Bias: The more we like someone, the more we are inclined to but from or help that person. We see people as pleasant if (a) they are outwardly attractive, (b) they are similar to you, or (3) they like you. This is why the salesperson copies body language and why multi-level marketing schemes work. Advertising employs likable figures in ads. If you are a salesperson, make people like you. If you are a consumer, judge the product independent of the seller and pretend you don’t like the seller.
- Endowment effect: We consider things to be more valuable the moment we own them. If we are selling something, we charge more than we ourselves would spend on it. We are better at holding on to things than getting rid of them. This effect works on auction participants, too, which drives up bidding. And late-stage interview rejections. Don’t cling to things, rather view them as the universe temporarily bestowing them to you.
A lactic sour wheat beer with guava from Yonkers Brewing.
TK Coleman, my coworker on the education team at Praxis, told his career journey story in two parts on the Isaac Morehouse podcast. It is worth a listen:
I’ve heard many parts of this story through working with TK, but I hadn’t heard the entire thing laid out. I immensely respected TK before listening to this, but hearing his early story just added to it further. Here are a few things from these shows that I find admirable:
- TK’s complete dedication to topics.
- How he unapologetically structures his life around his top priorities.
- How humble he is. He knows so much more than he lets on. The last time he stayed with Amanda and me, I assumed that he knew very little about cocktails because he didn’t drink and never hinted at knowing about cocktails when I talked about them. In this show I learned that he was a professional bartender for a while and dove into bartending with the same intensity that he dives into everything else. He is this way about everything. He knows so much, be he never flaunts it. He approaches everything as a learning opportunity and doesn’t let his current knowledge get in the way of learning something new. He told me that one of his pet peeves is that people prefer to talk instead of listen, so he tries his best to avoid that.
- He isn’t afraid to admit that he was scared and that stopped him from going to Hollywood at first. He always seems confident and fearless, so hearing this makes him seem more real. And even better.
Here are some of my takeaways from the two shows:
- It is okay to stick with a few things and do them seriously for a few years and then decide to move on to something else. Just don’t treat those two years as a half-hearted effort. Go all-in. You don’t need a grand life plan early in your career. When I think that the place I’m currently at in life is a huge deal, remember that there are multiple parts of TK’s story where he made something his life for two years, moved on, and now it barely comes up unless someone asks.
- Don’t celebrate or call your Mom until the check clears
- If your startup has a significant tech component, bring on a tech cofounder. Don’t rely on contractors for a core product.
- Never take money from someone unless you know they can lose it and be okay with it
- Never take money out of a place of desperation or powerlessness. Walk away.
- Doing something that you don’t need permission to do is the ultimate expression of power.
- When you are working for free or cheap, the expectations are low. It is easy to blow people away. When you get brought on full time, now all the things that were impressive before are expected.
- Leave things in a way that allows you to come back in the future.
- The best path forward is doing whatever you are doing now fully and with integrity.