Don't blindly trust what AI tells you, because it's often wrong and tends to speak with a lot of confidence even when he doesn’t fully understand the situation or have all the facts. It’s always a good idea to question its statements, double- check the information it gives you, and form your own opinion instead of accepting everything at face value, especially in situations where accuracy really matters.
I think one of the main risks is the lack of critical thinking it can generate in people. When individuals become accustomed to having everything done for them, there is a real possibility of losing important cognitive skills, such as the ability to search for information independently or to carefully analyze and evaluate the information they come across. This reliance can slowly erode one’s capacity for problem-solving and independent reasoning. For instance, when facing an important task or assignment, it is easy to be tempted to rely entirely on artificial intelligence to produce the work for you. However, I personally prefer to approach such tasks by first attempting to complete them on my own, putting in the effort to develop my understanding and skills. Only after doing so do I consider using AI as a tool for review or additional support. I believe this approach helps me learn more effectively and prevents me from becoming overly dependent on technology. Furthermore, there is also the danger of blindly trusting everything that artificial intelligence provides without taking the time to question, cross-check, or verify its outputs. This unquestioning trust can be particularly problematic in situations that require careful judgment or when the information has real-world consequences, as it may lead to errors, misconceptions, or decisions based on incomplete or incorrect data.
Over-relying on AI for daily decisions or tasks can create several important risks. One major risk is the loss of human judgement. When people depend too much on AI for choices, such as navigation, shopping or even some work or life decisions, they may stop thinking critically and trust the system even when it makes mistakes. Another risk which we may not realize is bias. AI systems learn from existing data and if this is biased the decisions made by AI can be inaccurate. This can affect areas like hiring, lending, or even social media content, reinforcing stereotypes without users realizing it. Additionally, technical failures can cause problems. If AI stops working or give incorrect results, people who depend on them may struggle to function without alternatives. Finally, overusing AI can reduce human skills, such as problem-solving and decision-making, this can make individuals less independent in their everyday life.
Excessive dependence on these tools in the medium to long term makes us forget how we used to carry out everyday tasks, with the risk that if they were to disappear or become less accessible (lack of internet, increased cost of use, not having devices to connect, etc.), we would be seriously affected. I compare the excessive use of AI for everyday tasks to people who use GPS daily, for example, to go to university or work, or on weekends to travel to their hometown or nearby cities. Without GPS, these people become lost and are unable to reach any destination, even if it is a familiar one. Being able to function autonomously without relying on external devices allows us to be self-sufficient, and if at some point we do not have access to them, our lives will not be severely impacted. Using AI for basic tasks makes us lose the habit of reasoning and thinking critically, of knowing how to manage on our own, and it makes us dependent on these tools or companies whose ultimate goal, logically, is to make money and not to provide knowledge altruistically.
The risks of uncritical AI use are real and complex – especially in the university context, where decisions have an impact on many stakeholders in research, teaching and administration. From the day-to-day work and the experiences gained within the framework of the Digital University Hub, five central risk areas can be identified: 1. Incorrect deductions and recommendations: AI generates plausible-sounding answers that are not correct for the specific target group environment. What applies to a general context does not necessarily apply to one's own institution or department/department. 2. Loss of critical thinking: The more AI takes over, the less we practice our own judgment. Especially in areas such as project coordination and knowledge management, this is risky in the long term. 3. Dependency and loss of control: If processes, protocols and decision templates are generated exclusively by AI, a dependency arises – even in the event of system failures or changes in providers. 4. Data protection and confidentiality: Sensitive data (e.g. personnel data, strategy documents) is often processed in the university environment. Careless use of AI can trigger data protection problems. 5. Lack of context sensitivity: AI does not automatically know the institutional context – culture, history, internal dynamics and specific rules of an organization remain invisible (depending on the basic data/assistants). The AI transformation therefore always requires awareness and support measures: The path from AI- enabled to AI-integrated and ultimately AI-first organization will only succeed if humans remain responsible and the right guardrails are set.
In my view, too much reliance on AI in day-to-day decisions poses several risks. First of all, I hand over decisions to other people – to systems whose functionality I often only partially understand. As a result, I lose self-determination and freedom, because I increasingly get used to suggestions, recommendations or automatic decisions instead of weighing them up myself. Although it is comfortable, it may simply make you lazy. If the AI constantly tells me what the "best" next step is, I take less time to reflect on my own priorities. In the long term, critical thinking is forgotten because alternatives, uncertainties or creative solutions are hardly actively thought through. Another risk is that decisions are too much related to the past and that habits become even more entrenched. AI is based on data from the past and tends to reproduce existing patterns instead of promoting new ones. This reduces openness to unconventional paths. After all, there is a danger that people will become more and more standardized, as their decisions are calculated on the basis of probabilities. Individuality, intuition and personal values could take a back seat – although they are precisely what make human decisions valuable.
I genuinely believe that it degrades one’s capacity for problem-solving and I cannot put my finger on what it is exactly without scientific proof. Spending your time focused on a problem you solve on your own is a way to create very strong neural connections. I can see the ravages of heavy AI (or tech) reliance, and I can see people falling slowly into incompetence, even faster than I anticipated.
Loss of critical thinking and professional judgment. Exacerbation of existing biases in personnel evaluations.
AI is great as long as you know how to use it. I've experienced over time some AI models become worse in a way that they start making more mistakes and provide wrong information sometimes. That's what I recommend not relying solely on AI for tasks that you are unsure about. Always double-check with different sources and verify the information the AI gives you to make sure it's correct. And of course, use your own brand and common sense and knowledge. The AI should be complimentary to it, it doesn't replace it.
I use algorithms on a daily basis to support my training activities. In the last 24 hours, one example is how an algorithm helped me adapt a “Human Bingo” game to fit the purposes of a training on radicalisation. It assisted me in restructuring the content, refining the prompts, and aligning the activity more closely with the learning objectives - making the exercise more relevant and effective for participants.
In the last 24 hours, algorithms have supported me in multiple small but important ways, often without me noticing at first. For example, when I checked social media, the content I saw was already filtered and prioritized based on my interests and behavior. This saved me time and helped me focus on relevant information. In my professional work, AI played a key role in researching destinations, doing quick and efficient analysis of data, and preparing presentations. It also helped me summarize tasks and provided practical suggestions that improved my decision-making and productivity. When I used maps or checked traffic conditions, algorithms optimized my route in real time. Even email filtering and spam detection quietly improved my workflow by organizing information and reducing noise. What is interesting is that most of these interactions feel natural and almost invisible. We don’t actively think about the algorithms, but they shape many of our daily decisions and significantly increase our efficiency.