Mitigating tech bias to boost user experience

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Fine-tuning bias in AI requires a delicate balance between personalisation and diversity. FILE PHOTO | POOL

The hottest trend in technology is artificial intelligence (AI). Every sector is striving to incorporate this technology into products and workflows. At the Mobile World Congress, one of the largest annual technology gatherings, AI took centre stage. From enterprise products driving operational efficiency and product discovery to consumer tech plays, which ranged from the anticipated to the novel, AI is everywhere. This interest and movement in AI is not surprising given the amount of funding that continues to pour into companies building at this edge. Even Microsoft is participating in multiple cap tables, keen to not miss out on any advances, regardless of the big bet already made with Open AI.

Today, I talk about the growing undertones heard on the sidelines of commercial conversations, that of bias. Bias is often portrayed negatively. However, as we continue to consume products and services that are technologically enabled, our sense of self-awareness tunes into the times we are living in. This means that conversations must be had to bring much-needed perspective.

Bias is the tendency to favour one thing over another, often based on personal experiences, beliefs, or societal norms. It is part of human decision-making and, by extension, the design and implementation of AI systems. Bias can be seen as a foundational element in shaping the user experiences we desire.

Consider, for example, a recommendation algorithm used by a streaming service like Netflix. This algorithm is designed to predict what movies or TV shows a user might enjoy based on their viewing history and preferences. However, this algorithm is inherently biased because it relies on past behaviours to make predictions about future preferences. If a user has predominantly watched action movies in the past, the algorithm may be biased towards recommending more action movies, even if the user may be interested in exploring other genres.

While this bias can lead to a more personalised and enjoyable user experience for some, it can also reinforce existing preferences and limit exposure to new ideas or perspectives. This is where the balancing act comes into play.

Fine-tuning bias in AI requires a delicate balance between personalisation and diversity, ensuring that users are exposed to a wide range of content while still receiving recommendations that align with their interests.

One way to mitigate bias in AI is through algorithmic transparency and accountability. By making the decision-making process of AI systems more transparent, developers can identify and address biases that may exist within the algorithms.

For example, researchers at MIT have developed techniques for auditing and explaining machine learning models to uncover potential biases and ensure fairness in decision-making processes.

However, it’s important to acknowledge that bias in AI is not always unintentional or benign. In some cases, bias can be deliberately built into AI systems, either consciously or unconsciously, leading to discrimination and harm against certain groups of people. For instance, a facial recognition system that is biased towards recognising one skin shade over another can perpetuate existing inequalities and reinforce systemic discrimination, particularly in areas like law enforcement and job markets. To address these concerns, it is essential to incorporate ethical considerations into the design and deployment of AI systems.

This includes diversity and inclusivity in data collection and model training, as well as ongoing monitoring and evaluation to identify and mitigate biases as they arise. Additionally, policymakers and regulators play a critical role in ensuring that AI technologies are developed and used responsibly and equitably, with appropriate safeguards in place to protect against misuse and abuse.

By striving for balance and incorporating ethical considerations into the design and deployment of AI systems, we can harness the power of technology to create a more inclusive and equitable future for all.

Njihia is the head of business and partnerships at Safiri Express. [email protected]

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