Tag: künstliche intelligenz

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Artificial Intelligence, Machine Learning, Data Science, Data Mining, and Statistics… what is the difference?

Artificial Intelligence (AI)

Artificial Intelligence refers to the broad field of computer science that enables machines to perform tasks that typically require human intelligence. An example in marketing is the development of intelligent chatbots that automatically answer customer inquiries.

Machine Learning

Machine Learning is a subset of AI that enables machines to learn from data and adapt without being explicitly programmed. In marketing, Machine Learning is used, for example, to predict customer trends and create personalized advertising content.

Data Mining

Data Mining is the process of discovering patterns in large datasets. It is an important part of Data Science and is used in marketing to identify customer segments and better understand target audiences.

Data Science

Data Science is the field that combines techniques from statistics, Machine Learning, and data analysis to extract insights from data.

Statistics

Statistics is the foundation for Data Science and Machine Learning. It deals with methods for analyzing and interpreting data. In the marketing context, statistics is used to analyze customer trends and test hypotheses, such as in A/B testing. Some people claim that Data Science is just statistics in a new guise. However, Data Science is more of a combination of statistics and computer science, as it also involves working with large datasets.

Overlaps and Differences

  • Overlaps: Machine Learning is a subset of AI and is applied in Data Science. Both Data Mining and Machine Learning use statistical methods.
  • Differences: While AI is a broad field with various applications, Machine Learning specifically focuses on learning from data. Data Science combines these techniques to derive data-driven insights.

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The End of Mass Employment

In the ZEIT of December 4, 2014, there is again a writing about alternative forms of economy due to the loss of jobs due to technology, this time in an interview by Uwe Jean Heuser with Jeremy Rafkin. It quotes a speech by Larry Summers from 2001, who said that the economy will see a new revolution like that of e-electrification, because marginal costs for video, audio and text information will drop to almost 0. Profits could then only be made through monopolies, but it was not yet known which system would replace market capitalism. This, according to Rafkin, is actually paradoxical, because the market economy would then have created the most efficient markets of all, but then there would be no more profits, so that an economy of sharing could emerge.

Furthermore, according to Rafkin, the Internet of Things is a tripartite division of the Internet into a communication network, an energy network and a transport network. By the transport network, he means, for example, car sharing. Sensors would create complete transparency. At the same time, long-established companies such as RWE & Co are suffering the same fate as the music industry. Rafkin also sees the danger that jobs could be lost and there could be a break in society. “The third revolution in the 21st century will put an end to mass wage and salary work. But that takes half a century. […] We can still offer mass employment for two generations because we first have to create the infrastructure for the super Internet of Things. [… Once this platform is up and running, it will be powered by analytics and algorithms and managed by a small group of supervisory boards.” Rafkin assumes that the rest of the people will then do more social work and so-called social capital will be created. For example, Thatcher & Co should be grateful for the fact that the social sectors had to learn to finance themselves. Where this leads, in my opinion, is written in many other articles in the ZEIT: It is cared for according to the cash situation in hospitals and homes, unnecessary operations, etc.

Keynes allegedly wrote as early as 1930 that technology will replace jobs faster than new ones can be created. Rather, one should embrace this opportunity in order to “free humanity from the soulless duties of the market”. We have already read elsewhere that this does not work as hoped for with the shared economy at the beginning.

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From man-machine becomes man against machine

Roman Pletter writes in the 29/2014 issue of ZEIT about the potential loss of highly qualified jobs due to ever-improving algorithms. In the so-called second machine revolution, machines can learn on their own (I already did something like this at Ask.com in 2006, on a very small scale…), but now it’s enough for more than winning in chess.

Which doctor can have read all the studies on a topic? Does a lawyer really know all the verdicts? Can a banker really take all the factors into account for a business? The computers could. We are already seeing harbingers of this development in online advertising: Instead of an advertising banner being placed on a website in a global galactic manner, an algorithm decides which user sees which banner in a fraction of a second using statistical methods. Based on data, algorithms can also learn which personality profiles are particularly suitable for certain tasks, so that personnel selection could be taken over by machines in the future.

The consequence of all these developments? What happens if the so-called middle class loses its jobs? The author of the ZEIT quotes an MIT economist: “Brynjolfsson pleads for states to rethink the old idea of granting their citizens a basic income in order to allow them to participate in the productivity gains.” I’m not sure if this has really been thought through to the end. Looking at the news, I have great doubts that anyone in the world is actually willing to agree on a new economic system. And what about all the countries on earth that are still far from advancing such a level of automation that their populations can no longer work? Or that are already dependent on the work of other countries anyway?

At the same time, you have to keep one thing in mind: We haven’t even reached the peak of the hype cycle yet, perhaps because the empty promises of the New Economy were not so long ago and people are no longer so gullible. Yes, the development will be exponential. But it won’t be as easy as you think.