When even Elon Musk – normally a champion of the human ability to improve its condition through material progress – backs the robots, we know we’re in trouble. But barely a year ago, back in 2017, he became fear-monger-in-chief of the artificial-intelligence apocalypse. “What’s going to happen,” he said, “is robots will be able to do everything better than us … I mean all of us.”
But a lot can happen in two years. A report just published by PriceWaterhouseCoopers should go some way to calming such hysteria. It argues that AI will create slightly more jobs in the UK (7.2 million) than it displaces (7 million). So rather than lamenting an apocalyptic tomorrow in which we are ruled by our robot overlords, a more useful way to think about the future would be to consider how we can interlace the strengths of machines with those of humans.
John Giannandrea who left his role as Senior Vice President of Engineering at Google, to head up AI at Apple, is already doing so. “There’s just a huge amount of unwarranted hype around it right now,” he says, “[much of which is] borderline irresponsible.” We shouldn’t be using it to match or replace humans, but to make “machines slightly more intelligent — or slightly less dumb”. He isn’t dismissing the potential of computers to radically alter the way we work, but is thinking about the ways it will do so in a slightly more nuanced fashion.
He knows that the better we understand the differences between the way people think and the way in which machines calculate, the better we can assess how to work with them. For example, unlike machines, humans typically lean on a variety of mental rules of thumb that yield narratively plausible, but often logically dubious, judgments. The psychologist and Nobel laureate Daniel Kahneman calls the human mind “a machine for jumping to conclusions”.
Machines using deep-learning algorithms, in contrast, must be trained with thousands of photographs to recognise kittens— and even then, they will have formed no conceptual understanding of cats. Small children can easily learn what a kitten is from just a few examples. Not so machines. They don’t think like humans and they can only apply their ‘thinking’ to narrow fields. They cannot, therefore, associate pictures of cats with stories about cats.
But, counterintuitively perhaps, the tasks humans find hard, machines often find easy. Cognitive scientist Alison Gopnik summarises what is known as Moravec’s Paradox: “At first, we thought that the quintessential preoccupations of the officially smart few, like playing chess or proving theorems — the corridas of nerd machismo — would prove to be hardest for computers.”
But as we have discovered, this isn’t true. Computers do these terrifically complicated things effortlessly. As Gopniks says: “It turns out to be much easier to simulate the reasoning of a highly trained adult expert than to mimic the ordinary learning of every baby.”
We are bound to learn more as we work out how our strengths can work in concert. Humans, for example, will employ inspiration, judgments, sense and empathy; computers will bring brawn, repetition, rules adherence, data recall and analysis.
The psychologist and computer scientist JCR “Lick” Licklider, mentor to John McCarthy who coined the term Artificial Intelligence in 1955, predicted this future harmony in 1960. Rather than speculate on computers achieving human-style intelligence, Licklider argued with remarkable prescience that humans and computers would develop a symbiotic relationship, the strengths of one would counterbalance the limitations of the other.
Lick said:
“Men will set the goals, formulate the hypotheses, determine the criteria, and perform the evaluations. Computing machines will do the routinisable work that must be done to prepare the way for insights and decisions in technical and scientific thinking. … the resulting partnership will think as no human brain has ever thought and process data in a way not approached by the information-handling machines we know today.”
It’s a far more productive guide to the future than alarmist preditions of ‘super-intelligent’ AI. The advent of AI is simply the latest in many phases of automation, each of which has begun with fear and ended with more jobs, economic growth and prosperity. Indeed, the history of automation since the industrial revolution shows us that the introduction of machines reshapes jobs, rather than replacing them. They take on the mundane tasks, as humans move on to more complex – often more highly valued and meaningful – work. New technology tend to eliminate tasks, not work.
The goal now is subtly shifting from building machines that think like humans, to designing machines that help humans think and perform better. Most work, after all, is comprised of a mix of tasks: some of which are better suited to humans and some of which could one day be done better by machines.
As the capabilities of machines grow, managers will redesign work to take advantage of the strengths of both their human workers and their machines. Last month, Nestlé announced a new automated plant in the Midlands in which German logistics giant DHL will be installing collaborative robots, or “co-bots”, that will work alongside humans to pack goods.
While on one level, AI is but the latest phase of a centuries-old process of automating human labour, on another, this new breed of machines can sense, learn and adapt in ways that far surpass previous technologies. And as a result, it will ask new questions about human exceptionalism and how work is best done.
Let’s not forget that the heavily automated production of the Model 3 Tesla ran quickly into delays prompting Elon Musk to make an interesting volte-face. “Excessive automation at Tesla was a mistake,”he wrote in April this year. “To be precise, my mistake. Humans are underrated.”
***
Five ways humans are collaborating with intelligent machines
1. Assigned work
Certain tasks in a human workflow are outsourced to a machine. The machine completes the task unaided, with varying levels of instruction.
- Industrial robots welding and spray painting car parts on a production line, while human workers perform other tasks like fitting the IP panels and custom parts. Industrial robots labouring 24/7 in ‘dark factories’
- Autonomous vehicles in fully autonomous mode on a motorway
2. Supervised
Decision making processes are automated, but under a human eye. This mode requires the machine to be aware of and communicate risks and unknowns to human users.
- Airline flights in which the pilot intervenes only in certain circumstances
- Autonomous vehicles, which require ‘driver’ oversight.
3. Coexistent
We will increasingly live and work alongside intelligent machines, sharing the same spaces, but focusing on separate task-flows. Machines in these scenarios must be able to effectively negotiate shared space and anticipate human intent.
- Pedestrians sharing paths with delivery robots
- Warehouse staff working in parallel with and alongside robots
4. Assistive
Machines that will help us perform tasks faster and better. They support particular tasks in human workflows, and will excel in on discerning human goals and learning their preferences.
- Writing assistants that suggest words and how to improve text
- Exoskeletons assisting factory workers in strenuous work
5. Symbiotic
This emerging mode of collaboration is a highly interactive and reciprocal. People input strategic hypotheses and the machine suggests tactical options.
- Chess teams comprised of humans and computers, which beat the best computer-only systems
- Adobe Sensei which automates tedious design processes, and generates options, giving the designer more time for creative tasks
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SubscribeProfessor Giesecke, much lauded in some quarters, of course says we will get however many cases we’re going to get, regardless. Lockdown just defers deaths rather than avoiding them. In which case, track and trace simply keeps the daily death count low enough not to frighten the natives.
The Government has been a little creative with testing stats but that became inevitable once the media decided to use them as a stick to beat the Government with, rather than as a route to understanding.
More millennials have passports than driver’s licenses… A single round trip flight from LA to London has nearly the same carbon footprint as driving a Toyota Camry for a year. But boomers are the “gas guzzlers”. ha.
We millennials are insufferable, self-serving hypocrites, ravenous for virtue-clout, pathologically hanging over a pool of water staring at our own reflections”except unlike Narcissus, we’re actually aware the face we are hopelessly in love with is our own, and we just don’t care.
Anyway, I’m off to the next march. where’s my placard
No doubt we should have a competent test and tracing system in place. NHSX does need to up its game and get the APP working and secure. Why not make it mandatory to download for anyone over 18 and under 70 and avoid quarantining international visitors?
Personally the trade off of the state knowing where I am and if I have tested positive that I am self isolating is a small price to pay to get the economy back on track – I fear people in general dont really understand what kind of economic hardship we are heading for and potentially more general social unrest if we dont get the country back to work…..
Now is the wrong time to be complacent as to where we are heading
Test, trace and isolate by consent is a wish that probably won’t come true. The so called successful countries in the East realised this and have draconian controls written into law that a western democracy simply wouldn’t accept. The country at large and to some degree fuelled by a facile media have turned from “can’t release the lockdown it isn’t safe” to “release the lockdown and move to 1m distancing” almost in the blink of an eye. It’s almost as if the country has has a road to Damascus moment where the damage to the economy is concerned. Is the cure now worse than the disease?
The control measures could be based on risk assessment and anyone who is even on nodding terms with the ONS data will know that the risk factors are around age and underlying health concerns in the main. Almost half of deaths occur to to over 80’s and the risk to under 19’s is negligible. The old and vulnerable (who may not be in the workplace anyway) can be locked down and the remaining population can be allowed to go about their business aware of the risks.
Looking at the ONS data today it is highly likely that excess deaths will be below the 5yr average when the next data is published next Tuesday and it already is in London. Similarly the ONS suggest the infection numbers are 1 in 1750. If we accept that as an average then where I live in the North East the population of Newcastle Gateshead Sunderland and the surrounding areas is ~1.9m. So if I go for a walk I have to find one of the 1085 infected people and get close enough to catch it in a huge geographical area. If Karl Friston is correct then that number becomes 216.
I’m surprised that the report from Cog-UK on the genomes of Covid-19 hasn’t been more widely publicised or discussed. Maybe it doesn’t fit the MSM narrative.
It remains to be seen how courageous the government will be.
In the ’50s and ’60s my mother worried that television would fry my brain and make me go blind, and that rock-n-roll would turn me into a juvenile delinquent. The never-ending narrative.
Isolate the vulnerable and let it go through the working age population in a controlled manner – minimises deaths and economic impact. whilst getting us to a position where we have herd immunity faster so the vulnerable can come out of isolation earlier. When you look at how few new cases there have been in London for weeks now despite protests and other mass gatherings it would seem London is already pretty close despite antibody results being a bit disappointing – there is clearly more to immunity than just antibodies.
Just look at the Swedish public health data.
https://experience.arcgis.c…
There the epidemic has virtually disappeared with only 10 new intensive care admissions a day and a similar number of deaths, down from a peak of around 50 ICU admissions and 100 deaths per day. All accomplished without prolonged and excessive infringement of civil liberties.
200 people under 60 have died in Sweden out of a populace of 10 million. That’s ~3 per 100,000 people in the young and middle-aged segments of the populace and actually more than two thirds of those deaths were in people over 50. No wonder the young people are taking to the streets.