5 artificial intelligence myths that prevent innovation

There are many myths about AI. However, these can lead to missed opportunities to find solutions to real-world challenges using artificial intelligence. These developments already provide support for a variety of tasks – be it business decisions in companies, improvements in health care or disaster risk management.

AI is only used for high-tech development such as robots or other products from science fiction films

Artificial intelligence is often associated with robots that will eventually serve us. But actually, AI is just another way of saying, “computers that use data to support people”.

But even today, numerous AI applications help us in our daily lives: Google Maps automatically guides us to the fastest way to our destination, some households use smart meters that independently adjust their power consumption, and the best spam filters in our e-mail Subjects work thanks to AI.

Even in business, machine learning can do many practical things, from helping you allocate resources to predicting and responding to customers’ future needs, to automating the hassles of doing things on the computer every day and the real thing Work holds off.
In addition, these AI tools are used outside of companies to help people.


So biologists work with Google’s “AI for Social Good” program to help KI identify whale song voices in thousands of hours of oceanography. This really time-consuming task does the AI ​​faster and more reliably than humans ever could.

Only developers and AI experts can create AI solutions

Increasingly, companies are working to make artificial intelligence more accessible: several technology vendors provide interfaces – called APIs – that allow any organization to integrate pre-trained AI systems into their own developments. So there are already numerous APIs that are used for image analysis.

To operate this platform you do not have to be a developer specialized in AI, but you can use it yourself after a short introduction.

Also interesting: Artificial intelligence needs creative intelligence

For an AI project you need a lot of data, especially your own

Data is an important part of AI development – it is the language with which a corresponding model interacts with the world. What is indispensable for an AI application, however, is a data-driven task – a challenge based on information.

However, these do not have to be in your own company. Numerous digital data sets are freely available and can be used by anyone.

The WildBook nature conservation app, among other things, searches YouTube for previously tagged wild animals using an AI that has been trained on the basis of this freely accessible data. In this way, researchers can track very specific specimens around the world. But not only raw data is available for free, but also well-maintained and annotated specialist data sets from various areas.

AI is a “set it and forget it” solution and works on its own

AI needs people, it needs skilled workers. One of the biggest misconceptions about AI is that because it carries the word “intelligence,” it simply works on its own. However, AI is just another tool that helps with work.

Just as machines are maintained, an AI must be regularly reviewed and maintained. This is essential for both maintenance and optimization of the algorithms. For this reason, some employees need to spend time and resources maintaining the AI ​​systems to reliably perform their tasks.

Tech experts and developers are the only key to a good AI

There are many stories about exceptional talents in the technology industry, which have almost single-handedly developed outstanding inventions. Unfortunately, this does not work and all these geniuses always had a team around them.

AI experts and developers are great at building the technological backbone – but only when they understand the content challenges. Professionals and experts are therefore the ideal support to tackle existing real challenges and to optimize the AI ​​tools for everyday work.

That’s why the organization, DataKind, helps companies and non-profit organizations bring together the right experts. DataKind sees AI and data science as team sports: professionals in a variety of fields are just as essential to development as tech experts. A developer could be seen as a key player in this team, but without the professionals facing specific challenges on a daily basis, it can not work.

Also interesting: Curse & Blessing: What we can expect from Artificial Intelligence

To further support the development of AI systems for society, Google.org, the philanthropic offshoot of Google, has launched the global AI Impact Challenge. This global initiative aims to inspire social entrepreneurs and non-profits to submit their ideas of AI developments to solving social and humanitarian problems. This gives organizations the chance to receive a share of the $ 25 million in prize money and support for Google Cloud offerings. Ideas and concepts can be submitted until January 22nd.

About the author: Stefan Ebener leads an EMEA-wide Machine Learning and AI team of experts as Google Cloud’s Customer Engineering Manager. In addition, he is a freelance lecturer in business informatics and deals with ML, AI and big data with the topic “Opinion Leader Identification & Management”.

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