Ideshini Naidoo - Ethical AI for a better world

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Understanding the Impact of AI on Society

In this rapidly evolving digital era, Artificial Intelligence (AI) is more pervasive than ever. Its power and potential are enormous - but how we harness it remains a topic of contentious debate. As technologists, we bear the weighty responsibility of shaping the world with intelligent systems that are ethical, safe, and beneficial to everyone.

Technology is neither good nor evil in and of itself. It's all in how people use it. The power of technology has always held a dichotomy. The same tools can be used for different, often contradictory, purposes. Yet, the difference today lies in the unprecedented speed at which technology is evolving. This makes it harder for societies and governments to keep up, making responsible use of AI more challenging, but also more crucial.

Getting to Grips with AI Ethics: The Three Big Challenges

AI ethics is a big topic. Notwithstanding its size and complexity, it is our responsibility to make a positive impact, no matter how small, in steering its direction. Three significant challenges arise when good intentioned AI goes awry: feedback loops, bias, and disinformation.

Feedback Loops: The Dark Side of AI Efficiency

Feedback loops are one of the most common unintended consequences of AI algorithms. An AI system learns and improves its function based on outcomes from past data. A prime example of a feedback loop is YouTube's recommendation engine. On surface level, the algorithm successfully optimizes watch hours, with 70% of content viewed on YouTube recommended by this engine. However, in misjudging the content as good or bad, it inadvertently endorses questionable content. Consequently, with users exposed mostly to specific kinds of content, misinformation can proliferate and potentially radicalize viewers.

Rather than resist the inevitability of feedback loops, we have to monitor their potential side effects carefully and be deliberate in the design decisions that we make. One positive example is from a lead machine learning engineer at Meta, who remedied gender bias by removing gender as a factor from the company's Meetup recommendation algorithm.

Addressing Bias in AI

Bias is another crux of responsible and ethical AI use. While biased data is often blamed for skewing AI-based systems and algorithms, researchers at MIT have identified at least six other areas where bias can seep into the AI machine learning process.

Two of such biases, historical bias and representation bias, frequently make their presence felt, frequently stemming from existing societal biases. To address these, algorithm developers must use diverse and curated data sets for training and testing AI systems, but also remember to build trustworthy AI systems by increasing transparency and explainability in the algorithms.

Disinformation: Shattering the Glass Box

Propaganda is not a new phenomenon; it's just more prevalent and impactful in today's hyperconnected world. Disinformation usually comprises half-truths, and often than not, seeds of truth taken out of context, making it powerful and dangerous as it confuses even the discerning mind.

In the face of disinformation, we must exercise discernment, verifying the sources of information before accepting them at face value.

Join the Fight for Ethical AI

In conclusion, the fight for ethical and responsible use of AI is one that we must all join. Making a difference begins with understanding the potential pitfalls and learning how to circumvent them.

At Thompson Reuters, we aim to play a crucial role in this global challenge and are always looking for like-minded individuals interested in making the world a better place through technology. If this resonates with you, consider joining our teams, where we tackle the great opportunities of our digital transformation program and delve into the realm of AI ethics.

Change begins with us - let's ensure AI technology is used to create a world that we'd be proud to have our names associated with.


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