How I’m Fighting Bias in Algorithms @TED #ted #shorts

TL;DR

I’m fighting bias in algorithms by promoting inclusive code, diverse full-spectrum teams, fairness during system development, and social change as a priority. Algorithmic bias can spread unfairness on a massive scale at a rapid pace, causing exclusionary experiences and discriminatory practices. Read on to see why who codes, how we code, and why we code all matter.

Transcript

Algorithmic bias, like human bias, results in unfairness. However, algorithms, like viruses, can spread bias on a massive scale at a rapid pace. Algorithmic bias can also lead to exclusionary experiences and discriminatory practices. So what can we do about it? Well, we can start thinking about how we create more inclusive code and employ inclus... Read More

Key Insights

• 🔎 Algorithmic bias, like human bias, can lead to unfairness and discrimination. It spreads quickly and on a large scale.
• 💻 Inclusive coding practices can help address algorithmic bias, and it starts with creating diverse teams that can identify blind spots.
• ⚖️ Fairness should be factored in during system development to ensure unbiased outcomes.
• 💡 People who code play a crucial role in combating algorithmic bias and promoting equality.
• 💰 Computational tools have generated immense wealth, but prioritizing social change can unlock even greater equality.
• 🤝 Creating full-spectrum teams with diverse individuals can help prevent algorithmic bias and exclusionary experiences.
• ⭐️ It is important to consider the impact of algorithms in perpetuating unfair practices and work towards more inclusive code.
• 🌍 By making social change a priority in coding, we have the opportunity to unlock greater equality and reduce discriminatory practices.

Questions & Answers

Q: How am I fighting bias in algorithms?

The approach is to create more inclusive code and employ inclusive coding practices. It focuses on who codes, how systems are coded, and why computational tools are created.

Q: How does algorithmic bias cause unfairness?

Algorithmic bias results in unfairness, just as human bias does. It can also produce exclusionary experiences and discriminatory practices.

Q: Why can algorithmic bias spread so widely?

Algorithms can spread bias on a massive scale at a rapid pace. The transcript compares this ability to the way viruses spread.

Q: Why does who codes matter?

Who codes matters because people are the starting point for more inclusive coding practices. Full-spectrum teams with diverse individuals can check each other’s blind spots.

Q: What is a full-spectrum coding team?

It is a team made up of diverse individuals. Those individuals can check each other’s blind spots while creating systems.

Q: How should fairness be included when developing systems?

Fairness should be factored in while systems are being developed. The transcript presents this as a central part of how people code.

Q: Why does the purpose behind coding matter?

Why people code matters because computational creation has already unlocked immense wealth. Making social change a priority creates an opportunity to unlock even greater equality.

Q: How can coding support greater equality?

Coding can support greater equality by prioritizing social change instead of treating it as an afterthought. Inclusive teams and fairness during development are also part of this approach.

Summary & Key Takeaways

• Algorithmic bias and human bias both result in unfairness, but algorithmic bias can spread rapidly on a large scale like viruses.

• Algorithmic bias can lead to exclusionary experiences and discriminatory practices.

• To address algorithmic bias, it is important to create teams with diverse individuals, factor in fairness during system development, and prioritize social change.