What are some examples of AI

What is Artificial Intelligence?

Artificial intelligence and humans

Like many new technologies, AI also fuels fears. A famous study by the University of Oxford in 2013 analyzed that 47 percent of all US jobs are at risk from automation, a significant proportion of them from AI. Such numbers stir up fears that lead to real actions: Waymo, the Google subsidiary for automated driving, reports that their test vehicles were attacked several times with knives and stones. So is AI a threat to humans? A bitkom survey paints a mixed picture: 62 percent of Germans see AI primarily as an opportunity, 35 percent as a danger. A survey of managers also found that 42 percent of them saw reservations on the part of the workforce.

The truth is somewhere in the middle. The AI ​​will undoubtedly take over manpower from humans, and if it does, then in full - that is, no human will be needed for this one task. These are mostly tasks with a rather low fun factor, monotonous and repetitive in nature: Watching surveillance videos, answering standard queries, searching through documents.

At the same time, however, new jobs will be created that will be supported by the innovative AI business models. People then have more time to use their manpower for new tasks because they work together with the AI. This would allow lawyers to spend more time with clients instead of digging through files for hours. It is also clear that more education is needed to prepare people for their new tasks and to give them the skills to work with AI systems.

And, to be honest, we don't really have a choice. Because AI has long since found its way into everyday life and almost everyone is already using it today, albeit unconsciously - whether on mobile phones, for transfers or for navigation. It will be some time before we encounter AIs everywhere, but that time will come sooner rather than later, because as soon as an area benefits from AI, it will have massive advantages over its human counterparts and thus displace them from the market.

Nevertheless, it is important to talk about it and ask yourself where the ethics are in the machine. This is not just about responsibility (“Who is to blame if the machine has an accident?”), But also the question of how we want to shape work in the future.

The natural stupidity in artificial intelligence

AIs are made by humans - and are therefore subject to a natural problem: an intelligence that mimics humans is also subject to their mental limitations. One of them is Bias, English for bias.

An example: In 2014, the AI ​​experts at Amazon developed an AI that automatically evaluated and sorted application documents. To do this, they trained the neural network with applications from the past ten years. When the AI ​​was trained, they found that the algorithm only selected those from men among new applications. Reason: There were an above-average number of men among those previously employed, as is usual in the tech industry. From this, the AI ​​created the rule: Only hire men. (Source) The mistake was in the selection and preparation of the data. Ultimately, Amazon rejected the experiment, and applications were still searched manually.

The example shows that when designing artificial intelligence, people have to attach great importance to the selection of representative data - and are aware that they may already be biased by selecting and processing the data. This dilemma is not an easy one and must be considered when designing an AI. This is another reason why it is worth taking a look from the outside, working with a partner and experts in the field of AI.

After all, every AI is programmed by a human - and we know where our intelligence begins and ends.

Finally, a short one Summary, about what artificial intelligence is:

  • AI is the attempt to transfer human learning and thinking to the computer
  • Strong AI, i.e. general problem-solving machines, belong to the field of science fiction, weak AI is being used more and more in today's world, whether in cell phones, in websites, social media or self-driving cars
  • AIs are valuable wherever a lot of data can be analyzed and researched for patterns
  • Machine learning is currently the most commercially important branch of AI
  • AIs need data as a basis; in addition to numbers, this can also be images, videos or sounds
  • AIs can process data better, more precisely and faster than humans, but they cannot understand it
  • AIs are only programmed ("trained") for very specific purposes and have to be retrained for other purposes
  • AIs will take over tasks from people, but at the same time also create new business areas and thus jobs
  • AIs cannot understand the data; if they are fed with incorrect data, they deliver incorrect results

Now that we have dealt with the basics, let's get down to the nitty-gritty: Find out what buzzwords like machine learning, neural networks or deep neural networks are all about and how an AI “thinks”.

Link tip: Free AI online course

The Finnish government has published an online course that provides an introduction to Artificial Intelligence that is understandable for everyone. In addition to basic knowledge, the course covers topics related to the "philosophy of AI", shows real application examples and deals with social issues.

The course is available in numerous languages, free registration at: https://www.elementsofai.de/

AI on your ears

In the podcast "Think Reactor" from Bremen, two experts, Roland Becker and Sirko Straube, regularly talk about burning questions about AI - whether it's about work, education, data protection or the like. They always remain generally understandable and also gently introduce newcomers to the complex topics.

Inis Honest

! ed.nemerb.haw [AT] hcilrhe.sini