The future of AI

This is a much-edited version of a presentation given at APEC’s recent “Industry 4.0: Enabling Technologies and Inclusive Digitization for Post COVID-19 Economic Recovery in APEC Value Chains” online conference. Jonathan Blanchard Smith, from SAMI, and Dr Gissella Bejanaro from Binghampton University (SUNY) presented on AI, and its future.

Hanson Robotics’ Sophia is what people think of when they think of artificial intelligence. “Sophia is simultaneously a human-crafted science fiction character depicting the future of AI and robotics, and a platform for advanced robotics and AI research. She is the world’s first robot citizen and the first robot Innovation Ambassador for the United Nations Development Programme.”

But what is the future of AI in the context of Industry 4.0? Looking to the future is vital for 2 main reasons – Industry 4.0 has happened, and will shortly be replaced by industry 5.0 … And what AI is now is different from what it will be.

It’s important to understand that Industry 4.0 is, essentially, industry now. The future is in its developments. We don’t have timelines for these – what we’ve done is set up a series of technology hurdles, and we’re describing periods as you overcome those hurdles.

INDUSTRY 5.0 is described as “people working alongside robots and smart machines”, and includes AI, Connectivity, Robotics and the development of such innovations as “Smart Cities”. Industry 5.0 is more human-centric than the process-driven 4.0.

INDUSTRY 6.0 evolves further. It is “Ubiquitous, customer-driven, virtualized, antifragile manufacturing”: customer-centric, highly customized, with hyper-connected factories and dynamic supply chains.

INDUSTRY X is where it all comes together: the nexus point of industry, AI, biotechnology, IoT: green, circular, cognitive manufacturing. All pervasive and truly revolutionary, this is where the future really lies.

Our first question is about business models. Currently, business model thinking is focussed on what we could call ideals. That is because industry is still struggling mentally with how to grip AI.

Reading the literature throws up ideals such as:

• Agile customer co-creation
• Technical standards
• Scalable ecosystem integration.

These are not easy concepts to grasp, still less implement. And I think there are some serious questions coming up about business models in relation to AI, and Industry 5.0 and beyond. In some cases, the changes to business models are going to have to be as revolutionary as the changes in technology.

AI does not happen in isolation. It is accompanied by the industrial revolutions we have discussed before: 5G, the Internet of Things, blockchain, and numerous other changes.

But it will be utterly revolutionary. David Vandergrift says, there is no sign of it capping out: “Anybody making assumptions about the capabilities of intelligent software capping out at some point are mistaken”  And as Bill Gates warns, “A.I. is like nuclear energy — ‘both promising and dangerous “; “it will change society in some very deep ways” Some aspects of us looking at the future are what those very deep ways are.

The future

AI will change the way we work. It will do some jobs better than we do. It is true that every technological change brings disruption, as old jobs are replaced by machines. It’s been like that since before the industrial revolution. But it’s also true that every technological revolution generates new jobs – there are more people in work after a technological change than before it. We imagine the same will be true, at least for the foreseeable future.

Some of the more conceptual processes we will have to deal with include

“The future of AI is the future of work” – essentially, what we anticipate using AI for is to complement human labour. Whether that replaces people, or, as in the evolution of “cobots”, complementary robots, enhances humans’ ability to work better, is currently moot. Smart manufacturing has the ability to remove people from the loop altogether, whilst producing better products at higher quality more consistently. “Conversational AI”, where the ability of the AI to understand natural human speech well enough, and answer questions intuitively enough, will replace people in some interaction tasks.

Smart cities give the promise of coordinated transport links, energy efficiency, and enhanced living standards. If AI is to be truly human-centric, one of its most beneficial impacts will be on the improvement of our urban environments. It is clear, though, that one of the largest conceptual problems humans will have to deal with when AI becomes properly embedded is the de-humanisation of so many functions – whether they be jobs, or simply person-to-person interaction.

Where will AI have the greatest impact in the near future?

In entertainment, there could be custom movies featuring virtual actors of your choice. “Sophisticated predictive programs will analyse a film script’s storyline and forecast its box office potential.”

There will be medicine tailored to your genome. AI algorithms will enable medical professionals to customize health care to the genes, environment and lifestyle of each patient. Diagnostic accuracy will increase, as will drug discovery. Nursing assistants may become virtual – or robotised.

AI will replace people in many vital tasks – assistants will help people stay independent and live in their own homes longer. AI tools will keep nutritious food available, safely reach objects on high shelves, and monitor movement in the homes of the elderly and differently abled. The tools could mow lawns, keep windows washed and even help with bathing and hygiene.

Equally, AI tools, robots and cobots could replace humans entirely in high-risk activities – mining, firefighting, clearing mines and handling radioactive materials.

Self-driving vehicles, and autonomous systems, will move from the drawing board to the streets, rails and perhaps even the air (if Boeing has its way). Inevitably, they will also move into law enforcement and onto the battlefield.

No discussion of AI would be complete without thinking about personal augmentation. Smart glasses, when they work properly – and they’re getting there – will soon be followed by smart contact lenses. Elon Musk’sNeuralink promises “ultra-high bandwidth brain-machine interfaces to connect humans and computers”.

And AI can compensate for illness: working with paraplegics to use nascent neuromuscular implants to help them regain the use of their limbs, as well as with the blind and deaf to help them approximate sensations of sight and sound.

The future is at this stage unformed, but there are indicators: Quantum Computing, Immersive Realities and Digital Twins. As we move from specialised AI to general AI to Artificial general intelligence, the opportunities, and risks, are endless.

Which takes us to ethics. AI is already used for facial recognition, mass data capture and analysis, social credit systems, and the honing of algorithms which direct social media consumption.

AI is built by people – who have biases, and feed those into the AI, which uses them to make its decisions. Understanding the effect of those biases is key – which takes us to the “black box problem”. Underneath machine learning is deep learning. And we cannot see it or understand how the machine comes to its conclusions.  AI technology doesn’t come with a moral code. It doesn’t ‘understand’ the output it provides the same way a human does. When an AI produces a biased result, it won’t notice. So, humans must instead — and that’s difficult to do when we can’t understand the reasoning behind the result.

The answer is explainable AI. The problem is we’re not there yet. As in so much around artificial intelligence, our future depends on trying to pry out what futurists call “the seeds of the future in the present”. We know what we have. We think we know where we’re going. The trick is going to be making sure that we, and our increasingly clever artificial intelligences, are aligned on that journey.

Written by Jonathan Blanchard Smith, SAMI Fellow and Director

The views expressed are those of the author(s) and not necessarily of SAMI Consulting.

Future-prepared firms outperform the average by 33% higher profitability and 200% higher growth. SAMI Consulting brings 30 years of experience delivering foresight, futures and scenario planning – enabling companies and organisations make “robust decisions in uncertain times”. Find out more www.samiconsulting.co.uk.

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