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Application challenges of AI and robotics

Maxine-Laurie Marshall — November 2017
Machine learning, AI and robotics are impacting business and society. ICR’s head of data science Dr Bissan Al-Lazikani, Markus Voss CIO of DHL Supply Chain, and AI professor Dr Franz Radermacher reveal how they are using these technologies.

Machine learning, robotics and artificial intelligence have moved on from simply being talking points to having a real impact on business and society.

Cancer research, for example, is a very human challenge that is benefiting from the application of big data analytics and machine learning. Thanks to major technology advancements in data collection, storage and analysis it is now possible to understand the complexities of disease at “an unprecedented level,” says Dr Bissan Al-Lazikani, head of data science at The Institute of Cancer Research (ICR), and that “has really revolutionized the way we do drug discovery.”

With its Knowledge Hub platform, the ICR is gathering petabytes of patient data represented as a massive graph that can be explored by researchers looking for patterns associated with different cancers, she explains. “We have developed machine-learning techniques and algorithms to analyze the comprehensive, integrated data and so come up with suggestions for the best targets to work on given a specific context. The algorithms learn from the examples they’ve seen before, so when they encounter a protein that is new to them they can tell us whether there is a chance that it might make a good drug target or whether it is likely to be a failure.”

It takes many years and several hundred hours of a scientist’s time to manually search for appropriate drug targets for an effective cancer treatment, she says – and there is a high chance they end up at the wrong answer. Using machine learning to make intelligent suggestions ensures the process is exponentially faster and more accurate. But there is also a high degree of serendipity. “Another important factor is that you will discover things that you would never have known before,” she says. “It’s hidden knowledge discovery that’s really the powerful result of machine learning.”
The rise of robotics

The application of intelligent, decision-making applications and devices is also showing high-impact results in more industrial settings, with logistics one sector on the verge of a revolution.

While programmable robots have been used for decades in industries like automotive, Markus Voss, CIO and COO for Supply Chain at Deutsche Post DHL, says the operation of such robots has been restricted to dedicated cages, separating them from people. “In a logistics environment there’s a lot of movement, so robots need to work alongside human beings and react quickly to the things happening around them,” he says.

Seeing huge potential for digital transformation in his sector, Voss is experimenting with robotics in several ways, from delivery drones to warehouse pickers. “We have automatic trolleys which follow an individual and take in all the physical work of carrying a big trolley round a warehouse.” Other robots are working on repetitive tasks such as the packaging of parts. “We’ve introduced these kinds of robots into our operations in a number of warehouses,” he says, “and the pilot has been very successful.”

Even though Voss is seeing early wins, the potential for the widespread use of robots in business is being heralded as both a boon for productivity and a major disruptor of human economic activity. And that points to the potential for an even more profound impact.
Maintaining control of AI

Dr Franz Josef Radermacher, professor of AI at the University of Ulm in Germany, sees the biggest risk is the potential for general purpose AI to develop into something that is outside human understanding and control. However, he insists it is also possible to avoid that “by developing artificial intelligence in a way that is human-centric — so that the whole design of those machines ensures they are orientated towards positive effects for humans.”

Avoiding the creation of AI that is outside human control will require the design of new global governance structures, says Radermacher. “We should have global governance that enforces rules of design which make machines human-centric and whatever intelligent machines are developed, their design and programming would not allow them to take a step outside this world of human-centric orientation.”

The notion that AI will create super-smart machines is undeniable. Radermacher acknowledges that we will ultimately create machines that can perform much better than any human in many aspects — they could potentially live forever, upgrade their own brains, colonize space, and so on. But he insists they will not be able to entirely match human capabilities, particularly with regard to the emotional capacity to feel.

“Up to now we have seen nothing similar [to the human brain or body] in artificial intelligence and it’s not clear for me whether machines will actually get there,” he says. “I do not see any good argument as to why humankind should give up its dominant position to something we create.”
First published
November 2017
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About: Big Thinkers of 2017
Insights from CIOs Jay Crotts of Shell and Markus Voss of Deutsche Post DHL's Supply Chain group, the former CEO of Citrix Kirill Tatarinov, academics Rita McGrath of Columbia Business School and Franz Josef Radermacher of the University of Ulm and head of data science at the ICR Bissan Al-Lazikani.

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