AI and bias
Debora Mendola
Regional Managing Director & CEO @ Transcom | Expert in Digital Transformation, CX Leadership, and Building Long-term Client Relationships
🎯 Bias in Artificial Intelligence: A Risk Not to Be Underestimated 🚨
Artificial intelligence is radically transforming our society, offering incredible opportunities and revolutionizing various fields, from medicine to finance, security to creativity. However, behind the promise of AI lies a risk that is still too often overlooked: bias.
Today this has been the topic of discussion in the Masterclass held during ElleActiv event by Darya Majidi , Roberta Russo and Marco Passarotto
But what are biases?
In simple terms, biases are prejudices or distortions in data or algorithms that can influence AI outcomes. If a system is “tainted” by bias, it risks making unfair, inaccurate, or even discriminatory decisions.
Why do biases exist in AI?
1️⃣ Biased training data: AI algorithms rely on vast amounts of historical data. If this data contains biases, the AI risks learning and replicating those same prejudices.
2️⃣ Opaque algorithms: Some AI models, like those based on neural networks, are often "black boxes," making it difficult to identify and correct biases.
3️⃣ Human choices: Every AI is designed and trained by people, who bring their own beliefs and biases, whether consciously or not, into the process. This can affect the entire AI development.
What are AI Bias risks
🔹 Gender and racial discrimination: Facial recognition systems that identify people of different ethnicities or genders less accurately.
🔹 Socioeconomic biases: Algorithms that tend to favor individuals of a certain social status in loan applications or job screenings.
How can we reduce biases?
✅ Diversify training data: Use datasets that represent all people and situations to avoid unfair generalizations. This is why it is important to create an inclusive culture and approach
✅ Increase transparency: Develop systems that allow tracking of decisions and understanding of algorithm functioning.
✅ Raise awareness: Developers and companies must be aware of the risks of bias and work to prevent it.
The Conclusion is the the potential of AI is immense, but to be used fairly and justly, it is essential to identify and mitigate biases. Only then can we build a future where artificial intelligence truly serves everyone.
Strategist in Sustainability & Mobility | Bridging Renewable Energy & Electric Vehicles | GRI ESG | P&L; Operations Director | Data-Driven Decision-Maker | Fortune 500 Leadership experience
12moGreat to hear from you, Debora Mendola! It’s true, the world of AI can be daunting—especially for those of us who found the pre-AI world challenging enough! Bias has always been part of the human experience, shaped by our unique backgrounds, cultures, and training, making our interactions refreshingly unpredictable. Imagine a world where everyone expressed themselves in the exact same way—now that would be… something, wouldn’t it? You’re spot on about humans bringing their own 'algorithms' into the AI they train—much like we see in the corporate world, where strategies and decisions often come flavored with a healthy dose of personal ambition. The beauty of AI, though, is that it learns from us all, broadening the influences it reflects, so it doesn’t just stay as it started. And yes, while those early AI models did mirror some old-fashioned biases, perhaps the answer lies in balancing these with genuine merit, rather than just swapping out one bias for another. After all, it’s not only AI that could benefit from a bit of objectivity. Still, exciting to see AI working its way into so many areas. Who knows—maybe someday it will even help us tackle that timeless puzzle: corporate bias itself.