
Trust me, I’m a robot: how to avoid the pitfalls of AI
The development and adoption of AI are fraught with potential hazards. Here’s how to avoid the pitfalls and ensure trust in your systems. ...
by José Parra Moyano Published May 7, 2025 in Brain Circuits • 3 min read
1. AI still lags behind human performance in certain areas. But at which of the following tasks does it outperform us?
a) reading comprehension;
b) image recognition;
c) language understanding.
2.What are the main benefits of digital twins (not digital avatars)?
3. Should you use GenAI-based tools like ChatGPT to analyze data?
(Answers at foot of page)
By leveraging big data and AI, industrial organizations can create a more integrated approach to energy management, optimizing resource use and reducing emissions. This can be done by:
As AI becomes more central to the success of industrial business, the value of contextual data will rise. Companies must explore not only whether (and how) employees should be compensated for the data they produce, but how this data can be organized and pooled for industry-wide insights. One way to organize is data collectives, a model that allows individuals to pool their data, gaining collective bargaining power with the companies that rely on analyzing that data. The benefit is not only to employees: companies benefit from regularly updated, high-quality, and relevant data.
To realize this mutual value, organizations need to raise the overall data literacy of leadership and workers to collectively derive the best insights out of AI. Data literacy enables workers to understand tech systems, helping them to determine which tasks they should delegate, and which they should not. This reimagines the contribution of employees to their organization. So far, employees have contributed with their time; in the age of AI-enabled or AI-dependent workplaces, their biggest contribution could be their data.
1. All of them. According to Time magazine, while AI is yet to surpass humans significantly in tasks such as handwriting and speech recognition, it outperforms us in many other areas, including these.
2. Digital twins – virtual, real-time models of a physical object, system, or process – can improve decision-making, enhance operational performance, streamline procedures, and lower production costs. Gartner projects that more than 40% of large companies will use digital twins for operational excellence by 2027.
3. Yes and no. You can use GenAI-based tools to write and run the code to analyze data. But you need to be very careful when prompting the system, such that it uses the language function to write coding language that it runs on the data. You can learn more about this in chapter 6 of this book.
Collaborative use of AI can drive sustainability while empowering both employers and employees through data collaboration, energy optimization, and workforce adaptation.
Professor of Digital Strategy
José Parra Moyano is Professor of Digital Strategy. He focuses on the management and economics of data and privacy and how firms can create sustainable value in the digital economy. An award-winning teacher, he also founded his own successful startup, was appointed to the World Economic Forum’s Global Shapers Community of young people driving change, and was named on the Forbes ‘30 under 30’ list of outstanding young entrepreneurs in Switzerland. At IMD, he teaches in a variety of programs, such as the MBA and Strategic Finance programs, on the topic of AI, strategy, and Innovation.
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