Ethics and AI: The responsibility of data scientists: We often come into contact with artificial intelligence (AI) in our everyday lives - be it in healthcare, recruiting or when a streaming service recommends the next film. But well-functioning AI applications must be trained in advance with large amounts of data sets. On the one hand, the more training data, the better. However, data quality is also crucial for the success of an AI application, as otherwise errors or prejudices can easily arise.

In the new episode of the HPI knowledge podcast Neuland “Ethics and AI: The Responsibility of Data Scientists,” PD Dr. Jessica Heesen, head of the research focus on media ethics and information technology at the Ethics Center at the University of Tübingen, and Prof. Dr. Felix Naumann, head of the information systems department at the Hasso Plattner Institute (HPI), explains what high-quality data is and what ethical problems can arise with AI systems.

The connections between AI, ethics, law and data quality

Both scientists are currently researching the connections between AI, ethics, law and data quality in the BMAS-funded KITQAR project . With moderator Leon Stebe, they talk about the far-reaching consequences of inadequate training data and discuss how the general public can be made even more aware of the topic and how greater data sovereignty can be promoted within society.

It is extremely important that certain values ​​are included in the development process in order to generate an AI application that is oriented towards the common good and that serves the benefit of society and not just large AI corporations.

“If the data collection process is already questionable, it is clear that the data is not neutral and that bias can occur during data collection,” says Heesen.

That's why it's particularly important to ensure quality features such as accuracy, completeness and diversity in the data with which an AI model is trained right from the start, even if this involves higher costs.

“What makes matters worse is that errors can often only be recognized later if an AI system was initially trained with inadequate data sets. “Due to the complexity of the models, we unfortunately only notice that something has gone wrong when we are using them,” adds Naumann.

One of the key skills for better assessing the scope, consequences and susceptibility to errors lies with data scientists. “There are many people responsible, but data scientists in particular have the best overview of the effects,” emphasizes Naumann. They can show how training data is written and what requirements should be pursued in terms of data quality and standards. Naumann adds that raising awareness of the issues of ethics and law in relation to AI systems is therefore important during your studies. In addition, society's general basic understanding of AI and machine learning will be essential in the future.

In-depth knowledge about the digital world, explained clearly and understandably - this is what the knowledge podcast “Neuland” offers with experts from the Hasso Plattner Institute (HPI) at: https://podcast.hpi.de , on iTunes and Spotify. Once a month at Neuland they talk about current and socially relevant digital topics, their research work and the opportunities and challenges of digital trends and developments.

Short profile Hasso Plattner Institute

The Hasso Plattner Institute (HPI) in Potsdam is Germany's university center of excellence for digital engineering ( https://hpi.de ). With the bachelor's degree program "IT Systems Engineering", the joint digital engineering faculty of the HPI and the University of Potsdam offers a particularly practical engineering computer science course that is unique in Germany and is currently being used by around 700 students. Based on this, you can set your own research focus in the five master's degree programs “IT Systems Engineering”, “Digital Health”, “Data Engineering”, “Cybersecurity” and “Software Systems Engineering”. The HPI always occupies top positions in the CHE university rankings. The HPI School of Design Thinking, Europe's first innovation school for students based on the Stanford d.school model, offers 300 places for additional studies every year. There are currently 22 professors and over 50 other visiting professors, lecturers and lecturers working at the HPI. It conducts excellent university research - in its IT specialist areas, but also in the HPI Research School for doctoral students with its research branches in Cape Town, Irvine, Haifa and Nanjing. The focus of HPI teaching and research is the fundamentals and applications of large, highly complex and networked IT systems. In addition, there is the development and research of user-oriented innovations for all areas of life.

Related to the topic: What is artificial intelligence?


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Notes:
1) This content reflects the current state of affairs at the time of publication. The reproduction of individual images, screenshots, embeds or video sequences serves to discuss the topic. 2) Individual contributions were created through the use of machine assistance and were carefully checked by the Mimikama editorial team before publication. ( Reason )