In a short time, IT has gone from being one of many industries, not infrequently considered nerdish, to becoming a vital social utility. Now, says Peter Werdenhoff at Hewlett Packard Enterprise, IT is becoming crucial to solving our most significant social challenges.
The IT industry carries a great responsibility on its shoulders. The days when IT was a separate industry and department, disconnected from ”the business” are gone. We’re entering a stage where, instead, information technology is vital to the solving of our most significant social challenges – but also for seizing of the fantastic opportunities that are within reach.
”Our industry is crucial. Regardless of whether it’s threats or problems, I cannot see one single area where IT isn’t necessary for addressing them,” says Peter Werdenhoff, sales manager at Hewlett Packard Enterprise, Sweden.
How will the next intelligent drug look? How can we travel more efficiently? These are just two of many examples of how IT has become crucial for quickly finding answers.
”There are lots of examples. Like, for instance, how specialist physicians can be made accessible to more clients by offering remote consultations, or how carbon dioxide can be trapped from the atmosphere efficiently. I cannot think of any area where IT couldn’t provide a solution,” says Peter Werdenhoff.
There are many reasons why IT has become critical for the solving of complex problems. Primarily, Peter Werdenhoff emphasizes the fact that information now comes from many directions and in enormous quantities. For the right decisions to be based on the deluge of information, IT is essential.
”To be able to run as fast as we need to, we must have a better and more intelligent infrastructure. That’s the only way of staying at the leading edge. So, what we can do for Sweden generally is to make a higher rate of innovation possible, based on this intelligent infrastructure.”
What’s quite necessary is that the infrastructure shouldn’t require spending lots of time on maintenance. That’s why it needs to be intelligent and autonomously able to adapt to the needs of the users. Not least, the system needs to be secure and proactive and also able to discover errors before they happen and to fix them.
This borders on machine learning, which many consider being AI: systems that are capable of learning over time.
”Today just about everyone is using that technology every day, without thinking about it. The wave of automation we experience now is unique in history, and of course, it comes with enormous benefits – but also with drawbacks.”
”Using an intelligent infrastructure, we can build AI services that some people would consider science fiction. But technology exists here and now. The transport sector may be the industry that receives the most publicity in the field of automation and AI. Self-driving cars and trucks exist on public roads, and in the long run, this means significantly improved traffic safety and lower costs.”
”But what will happen to all those who work in this sector? For sure, there is a shortage of drivers today, but it’s still only a few per cent. That’s nothing compared to what will happen when self-driving technology scales up and proves to be significantly more cost-effective than human drivers.”
Peter Werdenhoff believes that this is a shift that will happen very fast when, finally, somebody presses the start button. The simple reason is that AI is superior, so those companies that want to survive will need to change.
“We need data lakes. Now, we’re in some early-stage – data puddles.”
”This can be seen in other fields too. For example, tests are done with chatbots in homes for the elderly. They’re so good that the elderly will prefer talking to a bot to talking to a person. The bot continuously learns what kind of response each person prefers.”
”We can see a parallel development in the manufacturing industry where there is an increasing number of cases where AI does better than designers. One example is how Airbus uses AI for the optimal manufacturing of specific aircraft components, and AI design is superior to that of human designers, in terms of both strength and efficient use of materials. In the Netherlands, they’re using AI to design a bridge that’s better than the design made by humans.”
”This also applies to sustainability. AI can help you, for example, to design an engine to be as climate-friendly as possible. Logistics is another example where AI and machine learning can help finding processes and routes that are far more efficient than the current ones.”
These are significant social challenges and changes. Most of the technology already exists. What’s needed are political decisions to get the development going, says Peter Werdenhoff. But are politicians and other top-level actors aware of these issues?
”I think they are, and I can hear the discussion in many places. In our world, we are talking about how we need massive amounts of data for the technology to be applicable on a societal scale. We need data lakes. Now, we’re in some early-stage – data puddles.”
So there are, in patches, many contributions even now. Peter Werdenhoff mentions how banks are using machine learning to detect frauds, but there is no higher-level comprehensive AI that can discover large-scale patterns and optimize processes across an entire organization. Yet.
”We’re still at the crawling stage. We will take the next step when application-driven instances get going. When we begin to connect those instances, things will happen. Very positive and exciting things” says Peter Werdenhoff.