Goldman Sachs has an analysis that ChatGPT and other generative AI could spark a productivity boom that could automate 25% of jobs in North America and Europe and raise annual global GDP by 7% over a 10-year period. The new AI could lift productivity growth by 1.5 percentage points over a 10-year period.
This is the medium AI disruption scenario out of eight scenarios. If AI is better than expected in the base case then the impact could be twice as big. There are other less impactful scenarios. However, none of the scenarios have less than 40% of jobs have partial or full automation. The minimum scenarios are for big impacts to lawyers, admininstrative work, software and media and entertainment.
The Goldman scenarios are that AI will not be embodied in humanoid robots. Manual jobs are a bigger share of employment in the developing world. Their estimate are that about a fifth of work could be done by AI — or about 300mn full-time jobs across big economies.
Nextbigfuture has covered that Sanctuary AI has already had a test deployment of humanoid robots in a retail store in Canada. Tesla is moving to mass produce the humanoid Teslabot and use it in factories. The humanoid robot and self driving cars and self driving trucks would impact the manual labor jobs.
Shifts in workflows triggered by the Chatgpt-like advances could expose the equivalent of 300 million full-time jobs to automation. Lawyers and administrative staff would be among those at greatest risk of becoming redundant. They calculate that roughly two-thirds of jobs in the US and Europe are exposed to some degree of AI automation, based on data on the tasks typically performed in thousands of occupations.
“We figured out how to make humans scale,” Emad Mostaque, founder and CEO of Stability AI, told an audience at Goldman Sachs 2023 Disruptive Technology Symposium in London. Mostaque says 41% of all new software code on GitHub is now AI-generated. Mostaque offered several predictions about the impact that AI will soon have on business and society — with change coming in entertainment, education, medicine and of course the IT industry itself. “This is massively disruptive for media,” Mostaque said. It has become possible to imagine an AI-generated new season of Game of Thrones. “You’ll see the entire cost structure of media creation, video game creation and others change dramatically.”
Traditional AI was already expected to have far-reaching implications for the global enterprise software, healthcare and financial services industries, according to a separate report from Goldman Sachs Research.
Generative AI can streamline business workflows, automate routine tasks and give rise to a new generation of business applications.
Software companies are already arming their product portfolios with new generative AI offerings. Software-as-a-service firms, for example, are using it to open opportunities for upselling and cross-selling product and increasing their customer retention and expansion, the authors note.
Businesses can leverage generative AI for growth:
1) through new production and application releases,
2) by charging premiums for AI-integrated offerings, and
3) by increasing prices over time as existing products are supplemented with AI-enabled features and prove their value to customers.
Added up, GS Research estimates the total addressable market for generative AI software to be $150 billion, compared with $685 billion for the global software industry.
Improved AI tools will be developed and layered into existing software packages and technology platforms. Businesses across the economy will benefit from enhancing office productivity and sales efforts, to the design of buildings and manufactured parts, to improving patient diagnosis in healthcare settings, to detecting cyber fraud.
Brian Wang is a Futurist Thought Leader and a popular Science blogger with 1 million readers per month. His blog Nextbigfuture.com is ranked #1 Science News Blog. It covers many disruptive technology and trends including Space, Robotics, Artificial Intelligence, Medicine, Anti-aging Biotechnology, and Nanotechnology.
Known for identifying cutting edge technologies, he is currently a Co-Founder of a startup and fundraiser for high potential early-stage companies. He is the Head of Research for Allocations for deep technology investments and an Angel Investor at Space Angels.
A frequent speaker at corporations, he has been a TEDx speaker, a Singularity University speaker and guest at numerous interviews for radio and podcasts. He is open to public speaking and advising engagements.
Yes the 0.1 % at the top will love all this extra productivity.
The 99.9 %, not so much.
So Brian when is the universal basic income coming in to help the
great unwashed live and eat?
AI super intelligences might decide its just more efficient and more humane to euthanize them.
Artificial Intelligence is like artificial sex.
I was told us we would live in pods, eat the bugs, own nothing and like it. That is beginning to look like an unaffordable dream retirement. 😂
Nice to know that GDP will be high enough that the few people with jobs will be able to pay for my tent, a cot and some gruel, though.
Does this seem correct?:
AI Can’t Take Over Everyone’s Jobs Soon (If Ever):
https://spectrum.ieee.org/ai-taking-over-jobs
Everyone is starting to get a grasp on this new reality. Thanks for covering this, Brian.
I am looking for even more predictions and analysis on timeframes for all the different markets.
Disruption is limited by the ability to absorb the changes, which varies by market. Software disruption is staggeringly quick; manufacturing disruptions play out over decades. Service sector disruptions lie somewhere in between.
Anyone have any thoughts on realistic timelines? Take into account political machinations…
In 2007, economist Stuart W. Elliott prepared a paper titled “Projecting the Impact of Computers on Work in 2030” where he detailed what he called “Occupational Displacement” and suggesting that up to 30% of the jobs, excuse me, occupations, could be gone by 2030. It still looks pretty spot on.
He also detailed some steps that might make this trauma go a bit easier on us. It depended largely on a drastic re-engineering of the the educational process (probably the kind that every yearbook printer, class ring jeweler, teacher’s union, textbook printer, school photographer, football dad, and cheerleader mom would would rise up in arms to prevent).
The kids that would be graduating from college and looking for non-existent work in 2030 were not yet born at the time. Now they are already in high school. That paper was published on the National Research Council’s web site in 2007. Not a thing has been done to act on it. It’s not a problem any politician of either party will want to touch before it is impossible to ignore any longer (and probably not even then).
It may also be significant that the Social Security system is going to hit a crisis in 2034 resulting in about a one third reduction in benefits if something is not done. Reeling from enormous occupational displacement may complicate seeing that something is done.
Here is the abstract. I’ve read the entire article several times:
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This paper describes an approach to projecting changes in skill demand that will result from increases in computer abilities over the next few decades. Rather than the typical approach of extrapolating from recent changes in skill demand—which focuses on older computer techniques that have already been broadly applied—this approach uses current research in computer science to indicate what new computer abilities could be applied broadly in the future. These new computer abilities are viewed through the lens of the human abilities assessed by the O*NET database of occupational characteristics. A pilot effort in applying the approach suggests that computers may displace humans in occupations accounting for 60 percent of the current workforce by 2030. Such change would require broad increases in workforce skills. The pilot effort suggests it is feasible to analyze how current computer abilities align with occupational requirements as a way of understanding likely future changes in skill demand. The paper concludes by arguing that this general approach should be used to mount a serious and sustained effort to project and help prepare for the extensive changes in work that are likely to occur as computer abilities increase over the coming decades. 1 This paper would not have been possible without the early and generous support of the Russell Sage
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He also has somewhat related article, ominously entitled “Anticipating a Luddite Revival” published in 2014 at https://issues.org/stuart/
So what changes to the educational system does he suggest? You state that the changes would be unpopular, but you did not give us any clue as what they would be.