AI Offers Many Opportunities – But Critical Thinking is Key

By Simon Gomez, Head Data and Innovation LGT Group  

But according to Abraham Bernstein, Full Professor at the University of Zurich’s Department of Informatics, contrary to the current hype, artificial intelligence isn’t a new concept. This was just one of many interesting insights he shared with his audience during a recent presentation on artificial intelligence at a joint conference organized by LGT Bank Switzerland and the UZH Foundation - the foundation of University of Zurich.

He also explored the opportunities that AI brings with it, the challenges it presents for society, and why people should become critical thinkers and start questioning this rapidly evolving technology.

Origins of AI

The story of AI begins long before the digital age. People were always interested in how intelligence works. Magnus, a scientist in the 13th century, for example, believed that intelligence was an interplay of hydraulic pressures in our brains. «It was Alan Turing’s work during the Second World War, however, that catapulted humans into the modern era of AI.»

«Today, the possibilities of AI seem limitless»

Turing developed the Turing test, which assesses a machine’s ability to exhibit intelligent behavior indistinguishable from a human's. This laid an important foundation for the AI-related research being done today. And ever since the emergence of high-performance computers, the world has seen a massive acceleration in the widespread application of AI.

AI’s Myriad Possibilities...

Today, the possibilities of AI seem limitless. From cancer diagnosis and fraud detection to personalized learning programs, AI promises huge efficiency gains and advances in almost all conceivable areas. Take medical imaging, for example.

AI systems can recognize anomalies in X-rays and MRI images, which can help doctors detect diseases early. In the financial sector, banks are using AI to identify suspicious transactions and combat financial fraud. And in the education sector, adaptive learning systems powered by AI make it possible to tailor learning to the individual needs of each student.

However, the true value of AI lies not in its ability to replace human skills, but to complement them. By relieving people of routine tasks, AI makes room for creativity and strategic thinking.

...How it Works...

But how does AI learn? At its core, artificial intelligence uses three types of reasoning: inductive reasoning, deductive reasoning and analogical reasoning. In the case of inductive reasoning, models such as decision trees or neural networks are trained using large amounts of data.

«Although it has incredible potential, AI also gives rise to some tough questions»

Based on these examples, AI systems then learn to recognize patterns and rules and apply them to new cases. Deductive reasoning is when AI systems draw logical conclusions from known information containing facts and rules. Analogical reasoning, on the other hand, is what happens when AI systems recognize similarities between problems in known cases and use these to make inferences, which apply to unknown cases.

Image recognition is a good example of how AI systems learn: to be able to reliably classify objects, neural networks are trained using millions of images that they process according to a rules-based approach.

...and the Questions That Need to be Asked

However, although it has incredible potential, AI also gives rise to some tough questions, such as: How do we ensure that AI systems are transparent and act responsibly? How do we counteract the bias and discrimination inherent in training data? And how do we deal with the economic upheavals and the repercussions for the labor force that come with greater automation?

AI systems are increasingly making decisions that can have a major impact on people’s lives, such as whether or not a person is granted a loan or hired for a job. It is therefore very important to ensure that the decision-making criteria used are fair, ethical, and transparent.

«People must be willing to challenge their approaches»

Data protection and privacy are also critical issues, as AI systems require huge amounts of data, some of which is sensitive personal data. The rights of the individual must therefore be protected. At the same time, however, AI’s development must not be overly restricted. The other major concern, of course, is that automation through AI could result in the disappearance of entire professions.

These are all uncomfortable but unavoidable issues that affect society as a whole. It is for this reason that during his speech, Professor Bernstein repeatedly emphasized the importance of critical thinking in the age of AI. He believes that people need to understand these systems and their decision-making processes.

In addition, he believes that these processes should be questioned. According to Professor Bernstein, a person can only make good use of AI and fully exploit its immense possibilities if they understand what it is and how it works.

The Importance of Interdisciplinary Collaboration and Diversity

Another point emphasized by Professor Bernstein is how crucial it is for experts to collaborate across different disciplines. In the age of AI, cooperation must be interdisciplinary to tackle the complex challenges it gives rise to. People must be willing to challenge their approaches and beliefs and communicate clearly to ensure effective collaboration.

Having diverse teams of people with different perspectives is pivotal, as this fosters creativity and innovation. Professor Bernstein also pointed to the importance of ensuring a balanced social discourse that is neither fearful nor euphoric, explaining that the only way AI can be used for the benefit of all is if the associated risks and opportunities are considered objectively.

Education and training are also key in the age of AI: employees require ongoing training to ensure they can take on the new, creative work that AI is not able to do. In addition, schools and universities must start embedding digital skills and critical thinking in their curricula.

«This will enable us to navigate the changes without leaving employees behind»

In addition, lifelong learning supported by adaptive learning systems powered by AI must become the norm. This will ensure that everyone benefits from the technology. People and machines will increasingly work together. «As AI takes over many routine tasks, people’s work will shift to different domains.»

To support this shift, governments must introduce measures that, for example, support companies with the transition and incentivize them to reposition themselves. This will enable us to navigate the changes without leaving employees behind.

In parallel, we must create the conditions needed to develop a human-centered AI that respects our values and fundamental rights. Governments are therefore called upon to define clear parameters within which AI can further evolve. Supranational groups such as the Council of Europe, the EU and the OECD also have an important role to play in establishing global standards for trustworthy AI.

New AI Narrative: Taking a Responsible, Curious and Open Approach

AI is a fascinating journey into new realms – one that should be approached openly but also critically. Professor Bernstein’s message is clear: we should reap the benefits that technology has to offer, but should not allow it to develop indiscriminately.

We must be smart about AI and actively shape its further evolution. This will enable us to exploit its possibilities while minimizing the risks. Pioneering technologies require serious scrutiny – which is why we must be critical of AI. If we get it right, AI has the potential to improve everyone’s life and help us overcome many of the major challenges of our time.

We should therefore rise to the challenge by taking a responsible, curious, and open approach to this rapidly evolving technology.

Abraham Bernstein is a Professor at the Department of Computer Science at the University of Zurich (UZH), where he leads the Dynamic and Distributed Information Systems Group. He is also the founding director of the UZH Digital Society Initiative, which focuses on the intersection of society and digitalization and involves over 180 faculty members in various research projects.