KW 4: Frontline workers: The most important voice in artificial intelligence, The balance of AI regulation in politics, Artificial intelligence helps with Covid diagnoses


Frontline workers: The most important voice in artificial intelligence: Success with AI is going to be a bumpy and uneven road, and is going to need more human knowledge and input than we can ever imagine. At its core, artificial intelligence isn’t really a job-killer — it’s more of a taskmaster. While jobs will be lost, many more will be enhanced, elevated, and created, says James Manyika, chairman of the McKinsey Global Institute. How should we prepare the workforce for the changes ahead — to encourage their involvement in the AI revolution, as well as deliver the skills needed to make it happen? Many jobs, for example, are frontline workers who don’t have access to many technology tools.

The balance of AI regulation in politics: Projects and research in the field of artificial intelligence are considered key technologies of the future and are therefore being heavily funded. However, politics should not neglect the potential dangers of such applications, warns media and technology ethicist Thilo Hagendorff. With AI, for example, programs can use profile pictures of people to infer their political, sexual orientation or personality traits with a certain probability. That is why an ethics advisory board (Public Advisory Board) was founded in Cyber Valley in Baden-Württemberg to help researchers reflect on ethical and social issues. It is the first and only time in the world that such a civil society platform has existed, said Ulrich Hemel, director of the Global Ethic Institute in Tübingen.

Artificial intelligence helps with Covid diagnoses: A medical project in Dortmund has developed an AI that helps doctors discover dangerous lung damage. The “Rad-Companion” project also helps with Covid-19 patients and is therefore met with worldwide interest. The learning software was preprogrammed with over 100,000 X-ray images of Covid infected people. On the X-rays, the software shows the diseased areas of the lungs. With a scale from one to ten, the program shows how certain the diagnosis is. The program offers important support, especially in the intensive care unit, where doctors look after 10-15 Covid patients at once, explains radiologist Karsten Ridder.

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AI can recognize Covid-19 by sound: Scientists at ETH Lausanne train algorithms that are supposed to help humans recognize and assign noises. Noises provide doctors with valuable clues for recognizing diseases: for example, the lungs of patients with asthma whistle. Lungs with pneumonia, on the other hand, murmur. People, including doctors, have trouble hearing this.

10 rising star startups from Slovakia to watch in 2021: Slovakia’s capital Bratislava has a small but buzzing startup scene, where its small population affords a tight-knit community that helps each other grow and prepare to scale internationally. There are many young Slovak startups to watch in 2021. iERP, for example, is on a mission to help any size business use artificial intelligence algorithms, whether that be to leverage data, to forecast sales, or know what your customers will purchase and when. Cleantech Fuergy, meanwhile, is on a mission to optimize energy consumption. Its automated energy management system allows users to significantly reduce energy costs.

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An algorithm correctly assigned the breathing sounds in more than 70 percent of Covid-19-positive patients and even recognized more than 90 percent of the healthy patients.


AI fairness is an economic and social imperative: Now that artificial intelligence is providing an increasing number of recommendations to human decision-makers, it is important to make sure that, as a technology, it is not biased and thus respects the value of fairness. Here’s the sticking point, though: since AI systems are built by humans, who collect the training and test data and make the development decisions, they can – consciously or otherwise – be injected with biases. This, in turn, may lead to the deployment of AI systems that reflect and amplify such biases, resulting in decisions or recommendations that are systematically unfair to certain categories of people. Tools to improve the explainability of AI models enable the identification of the reasons behind the AI decisions, and can therefore also be useful in identifying bias in AI data or models. However, technical aspects and solutions to AI bias constitute just one dimension, and possibly the easiest one, of achieving AI fairness.

AI-for-agriculture platform: As the global agricultural industry stretches to meet expected population growth and food demand, and food security becomes more of a pressing issue with global warming, a startup out of South Africa is using artificial intelligence to help farmers manage their farms, trees and fruits. Aerobotics, a South African startup that provides intelligent tools to the world’s agriculture industry, has raised $17 million in an oversubscribed Series B round. South African consumer internet giant Naspers led the round through its investment arm, Naspers Foundry, investing $5.6 million, according to Aerobotics. Cathay AfricInvest Innovation, FMO: Entrepreneurial Development Bank and Platform Investment Partners also participated.

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Prevention with the help of AI: The new EU project Intervene started on January 1st. It aims to use AI-based technologies on a large pool of genomic health data in order to be able to make statistical predictions about the individual disease risk and disease progression of common diseases. To this end, the Hasso Plattner Institute (HPI) has joined forces with 16 other research institutes. The project will last five years and is funded by the European Union’s research and innovation program with ten million euros.


„Don’t worry about a jobless future. It is not for many, many decades. What we should think about is how we manage the transitions and adaptations as we help workers cope with this.“
James Manyika, chairman of the McKinsey Global Institute.


Still too many risks present: The potential uses of artificial intelligence represent a trillion-dollar opportunity for banks. But automated credit decisions are still too risky. Many problems, especially many ethical ones, have yet to be resolved.

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