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When Will Governments Address AI Bias? A Critical Look at Accountability

Written by: Molly-Anna MaQuirl | Posted: 16-01-2024

When Will Governments Address AI Bias? A Critical Look at Accountability

This is an AI-generated image created with Midjourney by Molly-Anna MaQuirl 

Artificial intelligence (AI) has suddenly and seamlessly moved from the realm of science fiction movies into our day-to-day lives. We are starting to encounter it around every corner, whether it’s when we ask our voice assistants for the weather, when we get suggested our next binge-worthy Netflix show, or when we apply for a job or loan.

But as AI becomes ubiquitous, it's essential to discuss a pressing issue: bias. And, more importantly, what governments are doing about it.

AI Bias: What’s All the Fuss About?

In case you aren’t familiar, AI bias means that the predictions, decisions, or information given by AI systems aren’t always neutral.

They can reflect prejudices, either because of the data they were trained on, or the way they were programmed. This makes sense when you think about how AI develops its processing frameworks, which are programmed by people. And people have biases.

You could look at it as a digital echo of society’s inherent biases.

This causes inequities to become codified into algorithms, leading to perpetuated or even exacerbated societal divisions.

For example, imagine an AI system that screens job applicants. If the data used to train this system comes primarily from male candidates with a certain background, it may unintentionally favor male applicants who have the same background. This could cause a lack of diversity and inclusion in hiring.

There are many other areas of concern when it comes to AI biases, some of which are currently getting very overlooked. Some AI bias examples are:

  • Healthcare: Think about AI systems that help doctors diagnose diseases. Now, if these systems mainly learn from the health data of a specific group, they might mess up when diagnosing someone from a different background with minor but key genetic differences. This can lead to patients not getting the right care they need.
  • Credit and Loan Approvals: Banks are now using AI to decide who gets a loan or credit. There are possibilities that prospects could be turned down, not because of their actual credentials, but because the AI has some preconceived notions based on race or where they come from.
  • Surveillance and Law Enforcement: Facial recognition tech is currently undergoing widespread adoption, but what if it can't recognize faces from certain ethnic backgrounds? That's not just an inconvenience; it is AI racial bias on full display, and it can result in innocent people being wrongly accused.
  • Education: AI tools are already being explored to help students learn. However, if these tools are biased, students may be receiving skewed information. What if all the students are being taught political science by AI that is biased towards one party, or if they are being taught health sciences that is based on the optimal health of people from one geographical region?
  • Social Media: This is something you have likely already experienced. How often do you only see content or news come up on your feed that you agree with or that's "typical" for your background? AI news biases and algorithms can be like being in a bubble, and that bubble can get pretty rigid, leading to more divided opinions and less understanding of different viewpoints.

Why Governments Must Step Up with AI

While it’s true that everyone has got a part to play in the AI story, governments have arguably  the biggest role. It is their responsibility to make sure that the story of AI ends up being one of fairness, justice, and inclusivity.

Here are a few things governments are responsible for when it comes to AI regulation and AI bias:

1.    Upholding Rights

  • Governments are the shield for our fundamental rights.
  • If AI shows bias, it's infringing on these rights. The government must step in.

2.    Keeping Tech in Check

  • Profit priority might make companies overlook ethics.
  • Governments need to be the ‘big brothers’ here, ensuring no one is cutting corners.

3.    Voice for the Voiceless

  • Not everyone has the ability to voice their concerns about AI or shout out against its wrongs.
  • Governments need to be the megaphone for these quieter voices, especially the most marginalized.

4.    Demystifying AI for the Public

  • AI is a confusing and misunderstood term to most of the general public.
  • It’s the government’s job to break it down into accessible terms and keep everyone in the loop.

5.    Thinking of Tomorrow

  • Today’s AI choices are tomorrow’s realities.
  • Governments need to have an eye on the future, making sure we’re setting up a fair and safe world for the next generations.

The Government’s Dance of Regulation

Typically, governments are playing a game of catch-up game with technology. As innovation races forward, legislative and regulatory frameworks usually lag behind. This delay isn't always due to a lack of understanding or will, but often because creating nuanced and effective policies requires time and research.

As the tech community has started to take active steps to begin grappling with biases in artificial intelligence, eyes are inevitably starting to turn to governments.

The stakes are high, and some governments are starting to recognize this and take action.

  • Legislative Initiatives: There's a growing understanding of AI's potential risks among policymakers. In response, governments are starting to create AI-specific task forces, with the aim of understanding the tech and its societal implications better.

Some nations have already started to move to introduce legislation focusing on AI transparency, accountability, and bias prevention.

  • Global Collaborations: Recognizing that AI is not confined by borders, several governments are pushing for international standards and cooperative frameworks. Collaborative strategies ensure that AI practices and policies are harmonized across regions.

Governments are beginning to seek out the expertise of those on the front lines of AI development, from all nations. Workshops with tech companies, forums with AI experts, and alliances with academic institutions are becoming more common.

  • Pilot Programs: Some governments have begun to initiate pilot programs, adopting AI in public services to understand its workings and implications firsthand. This hands-on approach greatly aids in shaping more informed policies.
  • Partnerships with Tech: Governments are now realizing the importance of working alongside tech giants, startups, and academic institutions. These budding partnerships aim to foster an environment where innovation thrives alongside responsible AI development.

The Challenges Ahead

There are many challenges that government bodies are currently facing and will continue to face in the future when it comes to addressing AI bias concerns.

  • Balancing Innovation and Regulation: If governments crack down too hard on regulations it might stifle innovation, but if they take a too relaxed approach it could fail to address the core issues of bias and fairness.
  • Interpreting AI Ethics: One of the most challenging aspects of developing unbiased AI is settling on a universal definition of what constitutes "bias" or "fairness”. Writing a definition that respects cultural, societal, and individual differences is a monumental task.
  • Enforcement: Setting guidelines is only one half of the puzzle. It is also a very difficult task to put into place enforcement efforts to ensure that companies and developers adhere to them consistently.
  • International Collaboration: AI doesn't recognize borders. Companies operate globally. Hence, isolated country-specific regulations might not be the solution.
  • Evolution Speed: AI technology is advancing at a breathtaking pace, and unfortunately for governments, the legislative process is much slower. It will be a major challenge for governments to stay ahead of the curve and not end up creating legislation that is outdated as soon as it is implemented.

Final Thoughts

The dance between governments and AI is complex and nuanced. As AI continues to get more integrated into our societal frameworks, the responsibility that governments hold only continues to increase.

Governments must accept their responsibility in getting ahead of the AI curve and ensuring that AI remains safe and unbiased for the public. Although there are many challenges that governing bodies will face to make this a reality, some progress is already being made.

The hope lies in a future where governments and the tech community move in harmony, focusing on creating a fair and unbiased AI that helps progress humanity forward in the right direction.

Explore More News

When Will Governments Address AI Bias? A Critical Look at Accountability

Written by: Molly-Anna MaQuirl | Posted: 16-01-2024

When Will Governments Address AI Bias? A Critical Look at Accountability

This is an AI-generated image created with Midjourney by Molly-Anna MaQuirl 

Artificial intelligence (AI) has suddenly and seamlessly moved from the realm of science fiction movies into our day-to-day lives. We are starting to encounter it around every corner, whether it’s when we ask our voice assistants for the weather, when we get suggested our next binge-worthy Netflix show, or when we apply for a job or loan.

But as AI becomes ubiquitous, it's essential to discuss a pressing issue: bias. And, more importantly, what governments are doing about it.

AI Bias: What’s All the Fuss About?

In case you aren’t familiar, AI bias means that the predictions, decisions, or information given by AI systems aren’t always neutral.

They can reflect prejudices, either because of the data they were trained on, or the way they were programmed. This makes sense when you think about how AI develops its processing frameworks, which are programmed by people. And people have biases.

You could look at it as a digital echo of society’s inherent biases.

This causes inequities to become codified into algorithms, leading to perpetuated or even exacerbated societal divisions.

For example, imagine an AI system that screens job applicants. If the data used to train this system comes primarily from male candidates with a certain background, it may unintentionally favor male applicants who have the same background. This could cause a lack of diversity and inclusion in hiring.

There are many other areas of concern when it comes to AI biases, some of which are currently getting very overlooked. Some AI bias examples are:

  • Healthcare: Think about AI systems that help doctors diagnose diseases. Now, if these systems mainly learn from the health data of a specific group, they might mess up when diagnosing someone from a different background with minor but key genetic differences. This can lead to patients not getting the right care they need.
  • Credit and Loan Approvals: Banks are now using AI to decide who gets a loan or credit. There are possibilities that prospects could be turned down, not because of their actual credentials, but because the AI has some preconceived notions based on race or where they come from.
  • Surveillance and Law Enforcement: Facial recognition tech is currently undergoing widespread adoption, but what if it can't recognize faces from certain ethnic backgrounds? That's not just an inconvenience; it is AI racial bias on full display, and it can result in innocent people being wrongly accused.
  • Education: AI tools are already being explored to help students learn. However, if these tools are biased, students may be receiving skewed information. What if all the students are being taught political science by AI that is biased towards one party, or if they are being taught health sciences that is based on the optimal health of people from one geographical region?
  • Social Media: This is something you have likely already experienced. How often do you only see content or news come up on your feed that you agree with or that's "typical" for your background? AI news biases and algorithms can be like being in a bubble, and that bubble can get pretty rigid, leading to more divided opinions and less understanding of different viewpoints.

Why Governments Must Step Up with AI

While it’s true that everyone has got a part to play in the AI story, governments have arguably  the biggest role. It is their responsibility to make sure that the story of AI ends up being one of fairness, justice, and inclusivity.

Here are a few things governments are responsible for when it comes to AI regulation and AI bias:

1.    Upholding Rights

  • Governments are the shield for our fundamental rights.
  • If AI shows bias, it's infringing on these rights. The government must step in.

2.    Keeping Tech in Check

  • Profit priority might make companies overlook ethics.
  • Governments need to be the ‘big brothers’ here, ensuring no one is cutting corners.

3.    Voice for the Voiceless

  • Not everyone has the ability to voice their concerns about AI or shout out against its wrongs.
  • Governments need to be the megaphone for these quieter voices, especially the most marginalized.

4.    Demystifying AI for the Public

  • AI is a confusing and misunderstood term to most of the general public.
  • It’s the government’s job to break it down into accessible terms and keep everyone in the loop.

5.    Thinking of Tomorrow

  • Today’s AI choices are tomorrow’s realities.
  • Governments need to have an eye on the future, making sure we’re setting up a fair and safe world for the next generations.

The Government’s Dance of Regulation

Typically, governments are playing a game of catch-up game with technology. As innovation races forward, legislative and regulatory frameworks usually lag behind. This delay isn't always due to a lack of understanding or will, but often because creating nuanced and effective policies requires time and research.

As the tech community has started to take active steps to begin grappling with biases in artificial intelligence, eyes are inevitably starting to turn to governments.

The stakes are high, and some governments are starting to recognize this and take action.

  • Legislative Initiatives: There's a growing understanding of AI's potential risks among policymakers. In response, governments are starting to create AI-specific task forces, with the aim of understanding the tech and its societal implications better.

Some nations have already started to move to introduce legislation focusing on AI transparency, accountability, and bias prevention.

  • Global Collaborations: Recognizing that AI is not confined by borders, several governments are pushing for international standards and cooperative frameworks. Collaborative strategies ensure that AI practices and policies are harmonized across regions.

Governments are beginning to seek out the expertise of those on the front lines of AI development, from all nations. Workshops with tech companies, forums with AI experts, and alliances with academic institutions are becoming more common.

  • Pilot Programs: Some governments have begun to initiate pilot programs, adopting AI in public services to understand its workings and implications firsthand. This hands-on approach greatly aids in shaping more informed policies.
  • Partnerships with Tech: Governments are now realizing the importance of working alongside tech giants, startups, and academic institutions. These budding partnerships aim to foster an environment where innovation thrives alongside responsible AI development.

The Challenges Ahead

There are many challenges that government bodies are currently facing and will continue to face in the future when it comes to addressing AI bias concerns.

  • Balancing Innovation and Regulation: If governments crack down too hard on regulations it might stifle innovation, but if they take a too relaxed approach it could fail to address the core issues of bias and fairness.
  • Interpreting AI Ethics: One of the most challenging aspects of developing unbiased AI is settling on a universal definition of what constitutes "bias" or "fairness”. Writing a definition that respects cultural, societal, and individual differences is a monumental task.
  • Enforcement: Setting guidelines is only one half of the puzzle. It is also a very difficult task to put into place enforcement efforts to ensure that companies and developers adhere to them consistently.
  • International Collaboration: AI doesn't recognize borders. Companies operate globally. Hence, isolated country-specific regulations might not be the solution.
  • Evolution Speed: AI technology is advancing at a breathtaking pace, and unfortunately for governments, the legislative process is much slower. It will be a major challenge for governments to stay ahead of the curve and not end up creating legislation that is outdated as soon as it is implemented.

Final Thoughts

The dance between governments and AI is complex and nuanced. As AI continues to get more integrated into our societal frameworks, the responsibility that governments hold only continues to increase.

Governments must accept their responsibility in getting ahead of the AI curve and ensuring that AI remains safe and unbiased for the public. Although there are many challenges that governing bodies will face to make this a reality, some progress is already being made.

The hope lies in a future where governments and the tech community move in harmony, focusing on creating a fair and unbiased AI that helps progress humanity forward in the right direction.