New-Tech Europe | February 2019

were more likely to re-offend than whites. All this has taught us that we need to look very carefully at the data used as input for AI systems. It also shows us that it is important for us to understand at all times how an algorithm arrives at a certain conclu-sion – and that we can make adjustments to it. The AI system cannot be a ‘black box’. New procedures and checks are required to ensure da-ta and algorithmic transparency. Yet it will probably not be possible to make all data input and algo- rithms transparent – which means there will be times when we do not know why an AI system may have come to certain conclusions. So it is important to introduce regular tests for AI systems, which include pay-ing a great deal of attention to ethical issues, so that any problems can be identified quickly. How can we trust ‘them’? So, how can we ensure that everyone is able to trust the AI system they come across on the workfloor, at the doctor’s surgery or on the road? First and foremost by allocating some sort of approval certificate, based on a regular audit of the system. One example of this are the elevators that we use every day. We have no idea about how their technology works, but we trust them to be safe and work properly (and we can do this because they are checked regularly by people who know what they are doing). The way humans and AI systems communicate and their predictability can also help to build a relationship of trust. For instance, take the traf- fic lights that we use to cross the road as pedestrians: they have a pushbutton that enables us to provide our own input (while a

Fig 4: We need to try and achieve the same level of trust in AI systems that we already have in smart traffic lights.

Will we still have a job in 2035? There is a good chance that many routine jobs will be taken over by AI systems and robots. That may range from working on a conveyor belt in a factory, to making certain medical diagnoses or working as an ac-countant or in legal jobs. Even tasks where a bit more creativity is re-quired can be carried out by AI

camera should also be able to detect the pedestrian anyway); we then receive a signal that our input has been registered; next, we wait patiently be-cause we know that we are using a predictable system that will turn green within a maximum of 2 minutes; and in some cases, the system even tells us how long we will have to wait before crossing.

Fig 5: Chess computers are a great example of what is possible with AI. They have gone so far that players can be suspected of using chess computers if the moves they make are strikingly original and creative.

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