Regulating Artificial Intelligence

Content

Our Newsletter

Get Our Resources Delivered Straight To Your Inbox

Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
We respect your privacy. Learn more here.

For business leaders, the advent of AI isn’t just a wave of innovation - it’s a double-edged sword. AI offers unparalleled opportunities for optimising operations, enhancing data-driven decision making and driving growth, but it also introduces complex challenges in compliance, data security and ethical decision-making. 

Stanford University’s AI Report found that in 2022, the AI focus area with the most investment was medical and healthcare ($6.1B), followed by data management, processing and cloud ($5.9B) and fintech ($5.5B).

However, without an understanding of the evolving regulatory landscape, these same capabilities could lead to significant risks, legal liabilities and ethical dilemmas.  For instance, a mistake in AI-driven data processing could expose companies to severe data breaches or misuse and turn a tool for growth into a potential liability.

Key Trends in Global AI Regulation:

Countries around the world are developing regulations for AI in a variety of ways.  Some are developing comprehensive legislation that will be enforceable in law, others are developing legislation for specific use cases and in some cases, there will just be guidelines and standards.

According to the AI Index Report 2023, the number of bills containing "artificial intelligence" that were passed into law grew from just 1 in 2016 to 37 in 2022 and mentions of AI in global legislative proceedings have increased nearly 6.5 times since 2016.

AI regulation is a complex area but certain key trends are emerging in draft regulations across the world:

Risk-Based Oversight

Regulations such as the EU’s AI Act, have opted for a risk-based framework that assesses the potential harm an AI system could cause and then imposes stricter controls on those systems deemed to be a higher risk.  

They have also implemented an outright ban on certain applications including social credit scoring, systems that manipulate human behaviour to circumvent free will and AI used to exploit the vulnerabilities of people (due to age or disability).  Any further AI regulation globally will likely take a similar risk-based approach to the EU’s.

Transparency and Explainability

There is a growing demand for transparency and explainability in AI systems, reflecting the need for users, regulators and society at large to comprehend how AI decision-making processes work.  The OECD lists transparency as one of their fundamental AI principles to promote the use of AI that is innovative and trustworthy.

The push for transparency and explainability is about demystifying AI systems and making their operations and decisions comprehensible to foster trust between the public and your organisation.  Data privacy, integrity and ethical data handling have been the zeitgeist for several years now; by implementing transparent and explainable AI models, you’re reinforcing a culture of accountability which is fundamental for AI deployment and maintaining your reputation.

Protection of Fundamental Rights

Safeguarding privacy, preventing discrimination and promoting equality are all central components of the world’s efforts to regulate AI. The majority of AI regulations suggest that any AI systems should be deployed in a manner that upholds human rights and aligns with core societal values.

While several nations are discussing AI regulations within their legislature, the EU, Canada, the USA and the UK are leading the way with the EU AI Act being signed into law on the 8th of December 2023.

How Does AI Regulation Impact Businesses?

AI has the potential to impact all industries, but some will feel the impact (and benefits) more than others.  Any business that implements AI needs to stay updated on AI regulations to ensure compliance with both national and international standards.

But let's focus on the healthcare industry, where AI presents both immense opportunities and significant challenges.

For business leaders in the healthcare sector, the responsibility they bear is using AI to augment patient care and operational efficiency while uploading the sanctity of patient data.  They have to balance leveraging AI for better patient outcomes without it becoming a liability. For AI implementation to be successful, you need a robust AI and data governance framework that will help you turn regulatory compliance into a strategic asset.

The primary concern lies in data privacy and security.  With AI’s capability to process extensive patient data, the risk of data breaches escalates, necessitating strict security measures and adherence to regulatory frameworks like HIPAA.  According to a recent Statista survey in the US, the primary concern surrounding the use of AI in healthcare was threats to privacy and security.

Compound this with the complexity of AI regulations and business leaders suddenly have an immense challenge: safeguarding patient data while enabling the transformative capabilities of AI to improve patient care.

There are also several ethical considerations with AI in healthcare.  Issues like decision-making in patient care, potential bias in medical algorithms and patient data consent would require businesses to engage closely with clinical and ethics boards to make sure AI applications align with the highest ethical standards. 

The global AI in healthcare market is expected to grow to $164 billion by 2029 and this highlights the need for organisations to balance financial expenditure against expected returns, including improving patient outcomes.

In the realm of healthcare, the ultimate goal is to leverage AI to enhance service delivery, maintain the trust and safety of patient data and align technological advances with the core values of patient care and data protection.

Conclusion

For business leaders, AI regulation is a critical frontier. Properly implemented, AI can propel businesses forward and provide unprecedented insights and efficiencies.  

However, mismanagement and non-compliance with regulations can lead to severe repercussions including legal challenges, security vulnerabilities and reputational damage and for industries like healthcare, the risks can be even greater.

The healthcare, finance, retail and manufacturing sectors will feel the impact of AI regulations more than others.  It's clear that businesses in all industries, including healthcare, need to consider the impact of AI on compliance, security, and data ethics. 

For those businesses that have already implemented AI, it's important to conduct a thorough review to ensure compliance with regulations. And for those that haven't implemented AI yet, it's crucial to take a strategic approach that prioritises compliance, security, and data ethics from the outset. By doing so, businesses can ensure that they're using AI to its fullest potential while also mitigating potential risks and liabilities.

Our Newsletter

Get Our Resources Delivered Straight To Your Inbox

Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
We respect your privacy. Learn more here.

Related Blogs

Fighting AI-Generated Identity Fraud: The Future of eKYC Verification
  • AI
  • February 20, 2024
Discover The Risks of AI-generated Identity Fraud
Navigating The Threat Of Prompt Injection In AI Models
  • AI
  • January 24, 2024
Learn About Prompt Injection Attacks In AI Models
Enhancing LLM Output with Retrieval Augmented Generation
  • AI
  • January 17, 2024
Discover The Secret To Great GenAI Outputs with RAGs
More Blogs

Contact Us For More Information

If you’d like to understand more about Zendata’s solutions and how we can help you, please reach out to the team today.
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.





Regulating Artificial Intelligence

December 12, 2023

For business leaders, the advent of AI isn’t just a wave of innovation - it’s a double-edged sword. AI offers unparalleled opportunities for optimising operations, enhancing data-driven decision making and driving growth, but it also introduces complex challenges in compliance, data security and ethical decision-making. 

Stanford University’s AI Report found that in 2022, the AI focus area with the most investment was medical and healthcare ($6.1B), followed by data management, processing and cloud ($5.9B) and fintech ($5.5B).

However, without an understanding of the evolving regulatory landscape, these same capabilities could lead to significant risks, legal liabilities and ethical dilemmas.  For instance, a mistake in AI-driven data processing could expose companies to severe data breaches or misuse and turn a tool for growth into a potential liability.

Key Trends in Global AI Regulation:

Countries around the world are developing regulations for AI in a variety of ways.  Some are developing comprehensive legislation that will be enforceable in law, others are developing legislation for specific use cases and in some cases, there will just be guidelines and standards.

According to the AI Index Report 2023, the number of bills containing "artificial intelligence" that were passed into law grew from just 1 in 2016 to 37 in 2022 and mentions of AI in global legislative proceedings have increased nearly 6.5 times since 2016.

AI regulation is a complex area but certain key trends are emerging in draft regulations across the world:

Risk-Based Oversight

Regulations such as the EU’s AI Act, have opted for a risk-based framework that assesses the potential harm an AI system could cause and then imposes stricter controls on those systems deemed to be a higher risk.  

They have also implemented an outright ban on certain applications including social credit scoring, systems that manipulate human behaviour to circumvent free will and AI used to exploit the vulnerabilities of people (due to age or disability).  Any further AI regulation globally will likely take a similar risk-based approach to the EU’s.

Transparency and Explainability

There is a growing demand for transparency and explainability in AI systems, reflecting the need for users, regulators and society at large to comprehend how AI decision-making processes work.  The OECD lists transparency as one of their fundamental AI principles to promote the use of AI that is innovative and trustworthy.

The push for transparency and explainability is about demystifying AI systems and making their operations and decisions comprehensible to foster trust between the public and your organisation.  Data privacy, integrity and ethical data handling have been the zeitgeist for several years now; by implementing transparent and explainable AI models, you’re reinforcing a culture of accountability which is fundamental for AI deployment and maintaining your reputation.

Protection of Fundamental Rights

Safeguarding privacy, preventing discrimination and promoting equality are all central components of the world’s efforts to regulate AI. The majority of AI regulations suggest that any AI systems should be deployed in a manner that upholds human rights and aligns with core societal values.

While several nations are discussing AI regulations within their legislature, the EU, Canada, the USA and the UK are leading the way with the EU AI Act being signed into law on the 8th of December 2023.

How Does AI Regulation Impact Businesses?

AI has the potential to impact all industries, but some will feel the impact (and benefits) more than others.  Any business that implements AI needs to stay updated on AI regulations to ensure compliance with both national and international standards.

But let's focus on the healthcare industry, where AI presents both immense opportunities and significant challenges.

For business leaders in the healthcare sector, the responsibility they bear is using AI to augment patient care and operational efficiency while uploading the sanctity of patient data.  They have to balance leveraging AI for better patient outcomes without it becoming a liability. For AI implementation to be successful, you need a robust AI and data governance framework that will help you turn regulatory compliance into a strategic asset.

The primary concern lies in data privacy and security.  With AI’s capability to process extensive patient data, the risk of data breaches escalates, necessitating strict security measures and adherence to regulatory frameworks like HIPAA.  According to a recent Statista survey in the US, the primary concern surrounding the use of AI in healthcare was threats to privacy and security.

Compound this with the complexity of AI regulations and business leaders suddenly have an immense challenge: safeguarding patient data while enabling the transformative capabilities of AI to improve patient care.

There are also several ethical considerations with AI in healthcare.  Issues like decision-making in patient care, potential bias in medical algorithms and patient data consent would require businesses to engage closely with clinical and ethics boards to make sure AI applications align with the highest ethical standards. 

The global AI in healthcare market is expected to grow to $164 billion by 2029 and this highlights the need for organisations to balance financial expenditure against expected returns, including improving patient outcomes.

In the realm of healthcare, the ultimate goal is to leverage AI to enhance service delivery, maintain the trust and safety of patient data and align technological advances with the core values of patient care and data protection.

Conclusion

For business leaders, AI regulation is a critical frontier. Properly implemented, AI can propel businesses forward and provide unprecedented insights and efficiencies.  

However, mismanagement and non-compliance with regulations can lead to severe repercussions including legal challenges, security vulnerabilities and reputational damage and for industries like healthcare, the risks can be even greater.

The healthcare, finance, retail and manufacturing sectors will feel the impact of AI regulations more than others.  It's clear that businesses in all industries, including healthcare, need to consider the impact of AI on compliance, security, and data ethics. 

For those businesses that have already implemented AI, it's important to conduct a thorough review to ensure compliance with regulations. And for those that haven't implemented AI yet, it's crucial to take a strategic approach that prioritises compliance, security, and data ethics from the outset. By doing so, businesses can ensure that they're using AI to its fullest potential while also mitigating potential risks and liabilities.