Künstliche Intelligenz und maschinelles Lernen für Einsteiger

1. 00:00In this unit we want to look at the general limitations of machine learning and artificial intelligence, before we go into individual aspects in detail.
2. 00:08In general, the following risks and problems exist on the topic of machine learning or artificial intelligence.
3. 00:16In general, there are errors that can cause the Data Scientists or machine learning experts can pass.
4. 00:22Potential for manipulation, misuse of data or problems, which result from a data monopoly situation.
5. 00:29The subitem Errors mainly refers to actual errors made by people, who work on machine learning models.
6. 00:36This involves issues such as spurious correlations, general bias or lack of objectivity in data analysis and for example the Simpson paradox.
7. 00:46With the Simpson paradox, for example, it seems, that the evaluation of different groups is different, depending on whether you combine the results of the groups or not.
8. 00:58If you do not pay attention to this, you can draw erroneous conclusions.
9. 01:02Manipulation refers mainly to the changes in results, to better represent the performance of the model.
10. 01:10For example, you can adapt your training to exactly those data, on which this is tested.
11. 01:17So the model seems to be super, but this is only the case for exactly these data.
12. 01:22But the model does not generalize at all against unseen new data points.
13. 01:27Of course, machine learning also carries the risk of being misused, either there is discrimination in data or one can discriminate through data
14. 01:38Monitoring and data breaches are also important and critical issues
15. 01:44Of course, large amounts of data and the associated value problems or social issues.
16. 01:53Is all data limited to only a few players such as a few companies, then these companies certainly have some power, because data can be seen as a kind of resource.
17. 02:05This often makes equal opportunities and aspects such as control difficult.
18. 02:10Aspects from these problem areas we will in the different videos still exemplary regard.
19. 02:19In general the following problems exist: The lack of knowledge as well as the lack of ethics and regulation.
20. 02:28The general solution is regulation, education and ethical guidelines, and a very general social discussion,
21. 02:37We will be working in the following units to some of the aspects just mentioned,
22. 02:45the importance of data and the limitations it imposes with the question what we really know, with the topic of discrimination
23. 02:54and also with the topic of ethics and morals in the context of machine learning.

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