Business and science are very interested in the question of how artificial intelligence can automate decisions. The general tenor at the specialist conference of the Münchner Kreis eV: Systems for artificial intelligence is changing how people make decisions. But people decide how and for what they want to use AI. “Provide orientation for dealing with artificial intelligence,”.
Around 180 participants accepted the invitation to the BayWa Congress Center on October 9th. They experienced an extensive program which, in addition to explanations on human decisions and how algorithms work in the AI environment, presented numerous examples of their practical use.
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Artificial Intelligence: Without Big Data, There Is No Helpful Technology
For example, they contribute to the energy transition by predicting electricity production in wind turbines. Automated creation of valuable texts in journalism and marketing and the evaluation and summary of scientific publications help to satisfy the constantly increasing need for information and, at the same time, channel the increasing flood of information.
Other applications and business models can, for example, reduce returns in the mail order business or support the establishment of functioning teams and networks. “How well AI makes decisions depends on the amount of data used. Looking at AI without big data is of no use. “
Machine Learning Is In The Foreground Of The Application
For a meaningful use of AI, so Lukowicz, users have to understand that today’s AI is above all one thing: The accumulation and organization of knowledge from vast amounts of data and converting the knowledge into action. Today, both are very much shaped by machine learning but also require important components from symbolic AI. So far, both have taken place in a clearly defined area for every application – and according to predetermined rules. For example, a robot that changes its pace after falling on a wet surface looks humanoid from a human perspective.
But the AI algorithm that controls it processes statistical functions according to basic mathematical principles with machine precision and speed, just like a chess computer. This model applies to all AI applications today. This also makes it clear: people determine what becomes of AI. Because they program the algorithms and select the data on which the algorithms are trained. In addition, they evaluate the results that AI systems deliver and assign the rights for their implementation.
Artificial Intelligence: Human-Machine Interaction Is In Demand
“Machines take over routine tasks and, in exceptional cases, delegate them back to people. But the situation overwhelms him because he has forgotten how to react adequately in such cases.” Using AI in companies, organizations, and society is not enough to introduce technology and then just press buttons. A look at the rebound effect of service robots, for example, suggests that, because of climate change, we should carefully consider which activities we transfer to AI systems because the use of service robots increases a person’s energy consumption many times over.
Therefore, it is essential to define the tasks of AI-controlled machines precisely and their role in humans. Different rules apply for the assistance robots to support physically disabled people than industrial robots.
Artificial Intelligence Is What People Make Of It
When machines relieve people of work, it has many advantages: It avoids damage to health from heavy physical activity under adverse conditions and enables more free time and self-determination. Nevertheless, many people currently fear the loss of their jobs, primarily due to digitization and AI. Many jobs will be lost in the next few years.
At the same time, however, digitization and AI are generating roughly the same number of new jobs in industrialized countries. Nevertheless, politicians must take action. This includes, for example, the increasing number of crowd working platforms to share in the costs of the social security systems.
Artificial Intelligence Is Developing In The Direction Of Autonomous Decision-Making
The immense potential of AI-based technologies is developing step by step towards autonomous decision-making. Willi Schroll from Strategic Labs-Foresight Services recommends adding three trends to the watch list: hyper-personalization, transparency, and quantum computing. Although AI surpasses classic programming in many areas, it is still a long way to market-ready products.
To build the necessary trust in AI, Konstantinos Stavrakis from PricewaterhouseCoopers GmbH presented a solution that, in addition to certificates based on quality and safety standards, also includes catalog-based audits and technology verification. “The success of AI will primarily depend on how it meets the expectations of users. As the Münchner Kreis, we will continue to help develop the potential of AI in such a way that as many people can use it as possible. “