Much more plausible and concerning, however, is that AI will stratify the labor force into 3 groups: highly-paid engineers (who manage the AI), highly-paid services job (i.e. doctors, lawyers, psychiatrist), and poorly-paid services job (i.e. barista).

This stratification has already happened as our economy advances (you mentioned baristas---in the past, those workers could have earned middle class manufacturing wages). The wage distribution in the services sector nowadays looks like a dumbbell [1].

Wage stratification can lead to political stratification as poor people don't have the resources to fight for their rights. Political stratification can lead to further wage stratification, continuing the cycle. That's why I believe that it's important to deal with the AI threat, now.

[1] https://seii.mit.edu/research/study/how-does-growth-in-the-u...

I disagree about stratification to a certain extent, that is, I only see 2 groups emerging. Here's my thinking.

Highly paid service jobs will remain unscathed only in so far as they have regulatory barriers to entry i.e. someone has to have gone to medical school, be licensed by a community of medical professionals, etc, in order to practice medicine. This applies to lawyers, doctors, psychiatrist, teachers, professors, architects but notably not to software engineers, carpenters, plumbers, etc (note: this split depends on country specific laws). Those fields that can simply block out or control the rate of progress and labor supply will see the least disruption in terms of wages. Also note, that most of these "future stable" fields are occupations which are tied closest to governmental law and regulation and are occupied by the upper echelon of society.

Occupations such as mail carrier, brick mason, railroad operator, gas station operator, steel worker, etc. which are currently well-paying middle class jobs, will evaporate over the coming decades in the face of innovation and automation due in large part to the absence of the ability to set arbitrary barriers to entry.

Within this "unprotected" category of jobs, i.e. those which cannot write regulations in law to protect themselves, those will persist for which it is simply more economical to maintain the status quo. Perhaps, something like a barista, or a part-time McDonalds worker or something of that sort. For these job categories, even though it may be feasible to have an android pour peoples coffee and bring it to their table and ask them about their day, people may dislike the service and/or the cost of producing such a product may simply be too high for that particular occupation.

This, I think, is how we should look at which job categories are more future / AI secure or not. Its at least the prediction metric I would use.

If however we're talking about the Singularity where artificial human-level intelligence is produced then I think this will be a more important discovery than fire or agriculture in the history of humankind. That means that we'll have produced machines that are as good or even probably better than humans at basically anything, from making coffee to driving a truck to being a bank teller to being a software developer. If we reach this point where humanity is basically obsolete then what happens?

I don't think the Singularity is as close as some people make it to be, I know AI is super hype these days but we've had AI winters in the past and they could happen again. I do believe that it's undoubtedly going to happen sooner or later however, be it in a year, a decade or a century. When it happens what are we going to do? Will it be the beginning of a heavenly post-scarcity world where super-intelligent machines take care of all our needs, freeing us to write poetry and do some soul searching or will it create an incredible amount of instability as all of humanity suddenly realize that whatever they want to do they can ask a machine to do for them and better?

Agree. Basically all current progress in "AI" should really just be called statistics and I think there would be much less confusion. If you say statistics meets Big Data and faster computers then you basically have all current progress. Real "AI" i.e. thinking machines which are behaviourally intelligent without resorting to cheap tricks has made very limited progress.

We might be able to fool ourselves into thinking a machine can think. For example, given a naive Bayes classifier for all X situations there is a probability that a real person responds with Y so therefore the machine responds with Y and then a human observing this system perceives the system to "be intelligent". But for me this is just statistics and nothing more, there is no abstract thought or intelligence going on within that machine system - at least as it relates to all other living creatures on the planet.

As long as we are useful we get to live to perform this duty. When no longer we'll become sausage.

Even if he was talking about the Singularity, I am skeptical of someone talking about a far-off, theoretical doom to discourage investment in competing existing technologies.

"Most notably, safety spans a wide range of concerns from the fears of sci-fi style sentience to the more near-term questions such as validating the performance of self-driving cars."

I feel like the term "Singularity" is used in too many ways by too many different people to be useful unless you define how you're using it but Brin seems worried about AGI.

That being said I'm very far removed from A.I. research so I don't really know what I'm talking about.

Because a lot of the new jobs were not automatable with the then-current state of technology. Over time, as technology becomes more and more sophisticated, more and more new jobs will be automated from the start.

> Since ATMs were introduced, the number of bank tellers in the US actually went up.

Would be interesting to know the background here, because this is massively counterintuitive. My guesses would be population growth and the increased complexity of financial products.

> AI is only as smart as the data you feed it. Even Google's own search rankings have to have human minders because people are too good at gaming their algorithms.

This is true for humans as well. Humans have a headstart here: We have thousands of years of experience in training humans, but only a few decades of experience training computers.

> AI is only good at the thing that human beings are very bad at - making quick, analytics based decisions.

AI is not the only piece of the puzzle. When combined with mechatronics, AI is good at another thing that human beings are very bad at: performing fast and extremely precise movements. When combined with advanced sensors, AI is good at another thing that human beings are very bad at: transcending human limits of perception (see e.g. LIDAR sensors in automated cars that can see things that a human cannot). And so on.

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I agree with your ending remarks though.

> Would be interesting to know the background here, because this is massively counterintuitive. My guesses would be population growth and the increased complexity of financial products.

With those things being automated, I guess banks had to find new ways to differentiate. Sales and relationship management are one of those domains that are highly difficult to automate and hence have a big potential for differentiation.

I see this all the time in related industries where firms are increasingly pushing towards “value added services” because they believe that those are difficult to replicate by competitors through machines (or otherwise). I believe the good news is that this will often indeed lead to higher capabilities and new products / services that people are interested to purchase (banks are maybe a bad example here)

- AI relies on data being available. For many professions there is simply no data to train an algorithm on, even when this would be a good fit for AI. An example I have in mind is skin disease diagnosis. We should start having generalist and dermatologists build a database of pictures and metadata of all the patients they see, even (and mostly) those that have nothing but just wanted to double check some suspicious spot. The only sort of database they have right now is collections of photos of the most pathological cases, but without the benign photos they are pretty much useless to build an automated AI diagnosis. Building this database might run against the incentive of the profession to be automated.

- AI is only economically viable above a minimum scale. The AI algorithm (and associated system) will not write or maintain itself. So you need to pay a team of software engineers to do that. That may or may not be more economical than paying a few people to do the job. We already hit that limit with software today. There is a lot of mundane office tasks that should have already been replaced with software but haven't.

- this one will be less popular here but I think is an important ceiling. There are many fields that software developers are completely uninterested in, and where the underlying business people are not technical enough to develop their own software. Certain areas of banking (outside of markets and retail), complex accounting rules, law, etc. The domain needs to be accessible to developers and that will make many professions very hard to automate even when they should. And the businesses may have no incentive to push for automation themselves (lawyers charge by the hour, they don't want more efficiency!).

Counterpoint[0]:

> But US bank teller employment actually rose modestly from 500,000 to approximately 550,000 over the 30-year period from 1980 to 2010 (although given the growth in the labor force in this time interval, these numbers do imply that bank tellers declined as a share of overall US employment).

[0] http://slatestarcodex.com/2018/02/19/technological-unemploym...

The doom-and-gloom scenario is when extremely adaptable and productive automation is deployed across many industries without time for the labor market to adapt, causing the world's population of 5-6 billion impoverished people to grow to 6-7 billion. Advancements in defense technology make it impossible for the masses to revolt and seize resources to revert to a pre-automation economy among themselves, so they die off.

A few hundred million shareholders and financiers enjoy their abundant luxury goods for a while, but they soon turn their robot armies against each other and also die off.

Certainly, if it becomes cost effective to have your fleet of vehicles operated by software instead of humans, a lot of people will have to find new jobs. "Truck driver" is the most commonly held profession in a majority of the fifty states.

Isn't that a bad thing?

While labor automation can be a boon for some and indirectly increase efficiencies, encouraging consumption of labor-intensive products and services directly incentivizes jobs creation. If this can be done in a safe manner (ie: appropriate workplace health codes and adequate protection against dangerous environmental externalities like pollution) then by all means it can be a good thing.

Regardless of your opinions on shifting manufacturing to China, it has lifted tens/hundreds of millions of people out of poverty and transformed the country into a consumer-based economy (from a largely agrarian society). While it has devastated/destroyed local habitats and caused other ugliness, it cannot be disputed that encouraging usage of labor on a massive scale has done a lot of good for the people of China.