The role regulators will play in guiding AI adoption to minimize security risks

As artificial intelligence (AI) has become increasingly popular across industries, its transformative power comes with significant security risks. AI is advancing faster than policy, while the rapid adoption of AI technologies has outpaced the creation of broad regulatory frameworks, raising questions about data privacy, ethical implications, and cybersecurity. This gap is prompting regulators to intervene with guidance on creating standards that mitigate risk.

The World Economic Forum report suggests that best practice guidelines are essential to maintaining systematic transparency, accountability, and social alignment in the design of AI systems. It is reasonable to assume that regulators will ultimately shape the use of AI, or more precisely, the strategies needed to mitigate security concerns. The overarching goal of regulators will be to create a safe and trusted AI ecosystem. This can be achieved by evaluating existing regulatory efforts and suggesting potential courses of action.

The Importance of Regulatory Oversight in the Field of Artificial Intelligence

Regulatory eyes should always be on the development and implementation of AI technologies. This should help future researchers, as AI systems that learn from such data without guidance can inadvertently perpetuate biases, resulting in unfair outcomes across industries. It could also have broad implications for hiring, lending, and law enforcement practices.

Machines too often perpetuate existing discrimination, and we need mechanisms to make sure that doesn’t happen. Regulations can enforce ethical standards to avoid potential risks and ensure fairness in the AI ​​world. Regulators are at the forefront of protecting this data and consumers’ privacy rights.

In Europe, regulations such as GDPR require companies to obtain explicit consent from users before collecting personal data. They also provide users with the ability to review, extract, or delete data upon request. Data breaches and misuse of data are difficult to prevent, so these compliance regulations are designed to protect consumer privacy and security.

Mitigating bias is important if AI technologies are to be widely accepted. This is where regulatory oversight comes in, to ensure that AI is safe, reliable and responsible, building that trust. People are more likely to adopt these technologies when they know that there are regulations in place to enforce responsible development and use of AI, preventing its abuse. Regulators are also expected to implement transparency and accountability standards, which could take the form of explanations of how their algorithms work for companies.

This transparency makes AI less mysterious and gives society confidence that these technologies are being used responsibly.

Key Regulators Involved in AI Governance

Regulatory bodies at the international, national, and industry levels are important for AI governance. Some of the key organizations involved in this effort include:

International organizations

1. Organisation for Economic Co-operation and Development (OECD)

The OECD established the AI ​​Principles to provide direction for AI that is human-centric, innovative, trustworthy, and respects human rights and democratic values. The Guidelines serve as a roadmap for such policies among member countries—to make AI work well for as many people as possible.

2. United Nations (UN)

The UN is working to develop global AI standards through agencies such as UNESCO. The guiding principle is to work to ensure that AI development is consistent with regulations on human rights, responsible development and ethical issues.

National Regulatory Agencies

3. US Federal Trade Commission (FTC)

The FTC’s mission is to protect the public from deceptive or unfair business practices and unfair methods of competition. It also works with other law enforcement agencies to implement interagency guidelines and agency-specific AI regulations.

4. GDPR: EU General Information Protection Regulation

GDPR is the law that applies in the EU. While it focuses primarily on privacy, it contains parts that are very relevant to AI, such as data collection, processing, user consent, and transparency. A reasonable interpretation of GDPR expands on this to ensure that AI systems respect the privacy and security of an individual’s data.

5. Financial Industry Regulatory Authority, Inc. (FINRA)

FINRA is described as a “self-regulatory organization (SRO) that oversees brokerage firms, registered brokers, and market transactions in the United States. Authorized by the Securities and Exchange Commission (SEC), FINRA creates the rules that brokers must follow, assesses firms’ compliance with those rules, and disciplines brokers who fail to comply.”

In the financial industry, the use of AI is closely monitored under the watchful eye of FINRA to ensure it complies with industry standards and regulations, monitors financial fraud using AI systems, and ensures that AI is open and fair.

Industry-specific regulatory bodies

6. Health Level Seven International (HL7)

In healthcare, HL7 is a “standards-developing organization dedicated to providing a comprehensive framework and related standards for the exchange, integration, sharing, and retrieval of electronic health information that supports clinical practice and the management, delivery, and evaluation of health services.” These standards are essential to ensuring the safety, effectiveness, and interoperability of AI systems in healthcare.

Non-regulatory guidelines

7. National Institute of Standards and Technology (NIST)

While not a regulatory body, one of the most respected bodies that issues guidance documents for technology professionals is NIST. These documents are often used as a basis for achieving compliance with regulations and standards. NIST offers detailed information on a variety of topics and currently hosts 2,190 documents related to information technology and 1,413 related to cybersecurity.

Going beyond regulations and standards

In addition to technical standards and regulations, ethical guidelines are key to guiding the responsible use of AI. Various guidelines, such as the European Commission’s Ethical Guidelines for AI, provide principles for the ethical development and deployment of AI systems. These guidelines emphasize transparency, accountability, and integrity, ensuring that AI technologies are used in a way that respects human rights and societal values.

AI Security Risk Mitigation Strategies

To protect AI systems from cyber threats, it is crucial to follow basic cybersecurity hygiene practices, such as using encryption to protect data, implementing secure coding practices, and providing regular updates and patches to fix vulnerabilities. All security experts emphasize that organizations that adopt comprehensive security protocols significantly reduce the risk of data breaches.

Conducting regular audits and compliance checks is essential to identifying and mitigating security risks across all systems. These audits help ensure systems are compliant with industry standards and regulations.

Transparency and accountability are key to building trust in AI technologies. Developers should openly communicate how AI systems are designed and used, and who is responsible for their performance. This transparency allows users to understand the potential risks and benefits of AI. At the recent World Economic Forum (WEF) conference, a common theme was that transparent AI practices lead to greater user trust and better risk management.

Challenges and opportunities for regulators

Balancing Innovation with Security: One of the most difficult tasks regulators face is finding the right balance between encouraging innovation while ensuring security. At the same time, AI technologies have the potential to deliver great advances and economic development.

On the other hand, AI systems also pose serious security holes when not properly managed. Regulators must therefore introduce security versus innovation at every level, ensuring that all its frameworks offer data and privacy protection.

AI is developing so quickly that it is possible that regular regulatory frameworks will not keep up with addressing public concerns. For example, the rapid acceleration of development may result in a shift between safety and ethical standards. To address this, regulators, governments and other market organizations will need to update guidelines and standards in line with the latest developments in AI. This type of proactive work can prevent problems from arising.

Regulators should work with industry stakeholders and experts to help ensure AI is socially beneficial. They can work together to gain insights and create comprehensive strategies that encompass both innovation and safety. This partnership approach also helps ensure that AI-related regulatory activity is as practical, feasible, and aligned with the real-world development and implementation of AI technologies as possible.

Potential impact of effective regulation

A key aspect of mitigating the risks associated with AI deployment is the role of regulators. Regulatory governance plays a key role in AI development and deployment—ensuring quality, security, and transparency in the design, architecture, and delivery of AI services.

Their work strikes a fair balance between innovation and safety to promote public trust in AI technologies. As AI technologies evolve over time, ongoing interaction between regulators, developers, and users will be required to address new challenges and opportunities and maximize the positive impact of AI on society. It is also fair to predict that AI-specialized regulators will become commonplace in this emerging technology frontier.

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About the author:

Micheal Chukwube is an experienced digital marketer, content writer and technology enthusiast. He writes informative, research-backed articles on technology, cybersecurity and information security. His articles have been published in Techopedia, ReadWrite, HackerNoon and others.

Editor’s Note: The views expressed in this guest article are solely the author’s and do not necessarily reflect the views of Tripwire.