//Hidden Edge Club Man plus Machine: Putting AI on the Map

On this occasion, our debate considered the potential business value that AI could add, and its likely disruption. We debated the existential threat, the level of investment in AI, and its potential in a wide range of industries. We spent time considering how AI will affect strategy and debated the differences between AI development in Asia and also in Europe. Our debate covered many more insights than we can cover here, but this document captures the discussion from a high level. As dictated by club rules, all quotes have been anonymised and no idea is attributed to any one person.

Hidden Edge Club The discussion topic // 02

//THE DISCUSSION TOPICAccording to McKinsey, Tech Giants like Google spent between $20bn and $30bn on AI in 2016. External investment in AI in 2016 was between $8bn and $12bn, with Machine Learning accounting for nearly 60% of this.

AI is now seeping into cars, homes, and hospitals.

So, why are some forward-looking IT leaders pulling the reigns back on AI within their organisations?

Stephen Hawking has said, “the development of full artificial intelligence could spell the end of the human race.” And entrepreneur Elon Musk has described AI as “our biggest existential threat”.

We asked:

l How can forward-thinking IT leaders determine whether they need an AI strategy? And what should this look like?

l How do we ensure our projects are successful when Gartner estimates that only 15% of AI projects will be completed?

l Are boards right to deprioritise other core objectives in favour of AI?

The debate ranged from world-championship Go players, to driverless trucks, and a new future for the insurance industry. We debated the myriad of dangers that could stem from AI acting independently, through to data, privacy and algorithmic transparency.

To kick off the debate, our Chair for the evening asked: how are you implementing AI now?

//THE DISCUSSIONOur chair for the evening was Finbarr Joy, Group Chief Technology Officer at Superbet. He’s an expert in building AI-powered platforms and specialises in product and technology strategy, development and operations for platform, network, technology innovation and IT. His prior roles drove technology transformation at global operators such as Lebara, William Hill & BT. His early experiences included 2 years with Netscape, as part of the team that brought the Internet to the world.

//A Watershed Year2016 was a watershed year for AI, Finbarr said, citing the first commercial delivery from a driverless truck, the possibility that Microsoft researchers may have developed speech recognition software to rival human parity and Google’s infamous AlphaGo beating a world championship Go player.

Finbarr attributed this success to three key factors:

l Cheap Parallel Devices

l An explosion of big data

l Evolution of better and better deep learning algorithms

However, this progress for a select few doesn’t mean that AI advancement is above question — or even that it’s possible for everyone. Organisations struggle to acquire employees with the right skills sets, while also having to answer difficult moral and cultural questions around proper AI development. Then, of course, you have the age old challenge of managing the dangers of AI acting independently. 

How are businesses meant to manage these challenges?  Finbarr argued for the need to develop a universal policy that is transparent, trustworthy, empathetic and fair.

Hidden Edge Club

//The Sci-Fi Dystopia Our first guest to speak told the club that he was working with algorithmics, machine learning algorithms and feedback loops. “It’s AI, but there is a huge gap between it and the sci-fi definition of AI,” he said.

He expressed doubt over the dystopian future described by Musk and Hawking, saying “That seems a long way off yet – although that might be because I don’t work where they do and I’m not seeing what they’re seeing!”

Another guest agreed, and shared an example of how machine learning algorithms are being used in the energy industry.

“We’re using deep learning to make safety decisions and the algorithms – the automated rigs – are doing it better than the manual crews. And they are more consistent; we don’t see the effect of a shift change, for example.”

//Real Business ApplicationsOne guest pointed out that AI is only ever as good as the data. “In the last four or five years we have got much better processing power, so we can deal with the necessary amount of data in real time.”

Our guest from the energy sector told us he is now looking at getting AI into other operational areas; working to mimic a human in terms of equipment diagnostics. It can even assess potential problems bsed on the sounds the machines make.

Another guest explained how AI is being used in the media industry to see how adverts perform and improve their scheduling. As well as tracking response in terms of time, day and channel, they are introducing new predictive capabilities that factor in weather, social events and news stories for dynamic scheduling that optimises returns for advertisers.

In banking, one guest identified opportunities in market innovation, managing operational risk, trends and customer behaviour. However, he wondered how far each could progress before the regulators catch up?

//Asia v. EuropeOne guest raised the question over the speed of progress, saying: “I fear there is an opacity about what is being done in China and Asia. There are fewer constraints, because there is no notion of privacy as we have in the West. We are more worried about the ethical boundaries, but whether they are always observed is another question.”

“There is one half of the world that is prepared to do anything and we won’t hear about it until it is released,” she continued.

“There is the danger that it becomes a race to the bottom,” agreed another guest.

However, another guest cited the example of Xiaoice, the AI weather forecaster with her own Weibo channel in China, a joint project between Microsoft Applications & Services Group East Asia and Shanghai Media Group (SMG) TV News Centre.

“It’s not only about looser regulations or less notions of privacy,” she said, “In China we have a real love for and fascination with technology; there is a desire to make it work.”

//The Way Forward?“Here in the West, we tend to see it as one or the other: machines or humans,” said one guest.

However, some were more optimistic: “I think technology will let us humans be even better than we ever could be without it.”

She referenced the AI Go player who beat the world champion; the former champion learned a new Go move from the machine.

However, this was contrasted with the experience of Tay, an AI bot based on the same technology as China’s Xiaoice. It took just 24 hours before it was corrupted by Twitter, started spouting racist hate speech, and had to be taken down.

There are some difficult questions still to be answered.

As our final speaker pointed out: “If you are raising something that people don’t fully understand, how are you going to control it?”

The discussion topic // 03

//THE CONCLUSIONThe Club united CIOs, CTOs, CDOs and other leaders from organisations in a diverse range of industries, including finance, media, energy, and insurance to debate where we should stand on AI and our investment in it in 2018. Debate on the night covered many more ideas and approaches than we can fully discuss here. To gain the in-depth insights that our guests benefited from, apply to join the group on our club site:

www.hiddenedgeclub.com

//Club PartnerWe would also like to thank our Club partner, SAS. SAS is the global leader in advanced analytics. Built on 40 years of experience, they help their clients discover hidden insights through advanced analytics in real-time. As a Forrester leader, and Gartner Magic Quadrant leader, SAS is widely recognised for its work in the machine learning space. UK clients include Nestle, Shop Direct, Allianz, RBS, Tesco, AstraZeneca, Vodaforne, BP, DWP, HMRC and more.

www.sas.com

Hidden Edge Club The discussion topic // 04THE CONCLUSION