What Is Trustworthy AI?

From costly errors in decision-making to high-profile cases of AI-driven bias and discrimination, the artificial intelligence systems we use today have demonstrated that they aren’t entirely reliable. And the fact that these systems are essentially unexplainable black boxes is fueling public skepticism even more. 

Consumers’ confidence in artificial intelligence is waning — and AI companies risk losing their audience unless they can prove their technology is trustworthy. A trustworthy AI system is one that makes decisions that align with human values, and can be depended upon to act fairly and consistently. It ensures that the technology operates as safely and transparently as possible, without making mistakes, reinforcing biases or causing any other kind of harm.

What Is Trustworthy AI?

Trustworthy AI is about more than just technical reliability, it also involves strong governance, a consideration of societal impacts and fostering a positive user experience. As AI becomes increasingly embedded in crucial sectors like healthcare, finance, transportation and criminal justice, ensuring its trustworthiness is essential for both its effectiveness and public acceptance.

There are several trustworthy AI frameworks offering guidance, with key contributions from organizations like the Organization for Economic Co-operation and Development (OECD) and the National Institute of Standards and Technology (NIST) in the United States, as well as the European Commission’s High-Level Expert Group on AI. Businesses can also implement strategies of their own to foster trustworthiness in their systems through responsible AI practices like documentation, continuous monitoring and data governance. Ultimately, building trustworthy AI begins with a conscious commitment from its creators. 

“Leadership has to fundamentally make a choice,” Brian Green, director of technology ethics at the Markkula Center for Applied Ethics at Santa Clara University, previously told Built In. “They have to say we want to be making technology that benefits the world, that’s not making the world a worse place, because we all have to live here together.”

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Principles of Trustworthy AI

The guiding principles of trustworthy AI vary depending on an individual organization’s goals and values. But frequently utilized principles of trustworthy AI include:

Fairness and Non-Discrimination

AI systems should be designed to prevent the perpetuation or amplification of biases based on race, gender, age or other attributes. Algorithms must be trained on diverse datasets and evaluated for fairness throughout their lifecycle.

Transparency

Trustworthy AI systems should be explainable and understandable to users and stakeholders. This includes clear documentation of how the AI operates, its data sources and its decision-making processes.

Accountability

Developers and deployers of AI systems should take responsibility for the responses their systems generate and the impacts those responses have on users. And mechanisms should be put in place to identify, address and mitigate issues as they arise.

Privacy and Security

Trustworthy AI must respect user privacy by ensuring data is securely handled and only used with explicit consent. Robust cybersecurity measures are necessary to prevent unauthorized access or malicious attacks.

Human Oversight

AI systems should augment human decision-making rather than replace it in critical domains. Keeping humans in the loop helps to ensure that AI is a benefit to society and aligns with human values.

Safety and Reliability

Trustworthy AI should perform consistently under both expected and unexpected conditions. Rigorous testing and monitoring are essential to prevent errors or harmful outcomes. Safe AI should protect human life, health, property and the environment. 

Social and Environmental Responsibility

The design and deployment of AI should contribute positively to society and the environment. This includes minimizing energy consumption, reducing emissions and promoting inclusivity.

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Why Is Trustworthy AI Important?

Developing trustworthy AI is important because artificial intelligence has permeated virtually every aspect of daily life, transforming the way we create, communicate and solve problems. AI is making decisions that directly impact people’s well-being and future —  if these systems aren’t trustworthy, they have the potential to make life-altering mistakes.

“Whether we like it or not, all of our lives are being impacted by AI today, and there’s going to be more of it tomorrow,” Senthil Kumar, chief technology officer at data analytics company Slate Technologies, previously told Built In. “Decision systems are being handed off to machines.”

For artificial intelligence to be accepted and trusted, people need to believe it is fair, reliable and safe to use. Otherwise, AI adoption will be limited, and its potential benefits may not ever be fully realized.

Trustworthy AI Framework Examples

In addition to the AI ethics frameworks from companies like Microsoft and Google, governments and other organizations have proposed guidelines for the development and deployment of trustworthy AI. Key frameworks include:

Blueprint for an AI Bill of Rights

Released by the White House Office of Science and Technology Policy in 2022, The Blueprint for an AI Bill of Rights seeks to protect individuals from potential harms associated with artificial intelligence and automated systems. Its principles include:

1. Safe and effective systems: Users should be protected from unsafe or ineffective systems.
2. Algorithmic discrimination protections: Users should not face discrimination while using these systems, and they should be designed in an equitable way.
3. Data privacy: Users should be protected from abusive data practices and they should have agency over how their data gets used.
4. Notice and explanation: Users should be informed when an automated system is being used to make decisions about them, and they should understand how and why those decisions impact them.
5. Human alternatives, consideration and fallback: Users should be able to opt out of using automated systems and be given a human alternative.

The European Union’s Ethics Guidelines for Trustworthy AI

Published in 2019 by the European Commission’s High-Level Expert Group on AI, the European Union’s guidelines emphasize a human-centered approach to future AI development. Its principles helped shape the EU AI Act, which governs the use of AI in the region. These principles include:

1. Human agency and oversight: AI systems should empower human beings, allowing them to make more informed decisions. And along the way there should be human oversight.
2. Technical robustness and safety: AI systems need to be resilient and secure, as well as accurate, reliable and reproducible.
3. Privacy and data governance: Beyond providing security and protection,the quality and integrity of data must be taken into account.
4. Transparency: The decision-making process of AI systems should be explained in a way that any given stakeholder can understand. And users should be made aware when they are interacting with an AI system.
5. Diversity, non-discrimination and fairness: Unfair bias must be avoided and AI systems should be accessible to all.
6. Societal and environmental well-being: AI systems should benefit all human beings now and in the future, which means it should be developed in ways that are sustainable and environmentally friendly.
7. Accountability: Mechanisms should be put in place to ensure responsibility and accountability for AI systems and their outcomes.

The OECD Principles on Artificial Intelligence

Published in 2019 by the international Organization for Economic Cooperation and Development (OECD), OECD’s AI Principles focus on democratic values and human rights. According to OECD, its principles are the first intergovernmental standards for AI. Nearly 50 countries have adopted the recommendations worldwide, including the United States, the United Kingdom and China. Its principles are as follows:

1. Inclusive growth, sustainable development and well-being: Developers of AI should seek to augment human capabilities and enhance creativity, advancing inclusion of underrepresented populations and reducing inequalities.
2. Human rights and democratic values, including fairness and privacy: Developers of AI should respect the rule of law, human rights and human values throughout the development and deployment process.
3. Transparency and explainability: AI developers should provide meaningful information (appropriate to the context) to help people understand the decisions their systems make.
4. Robustness, security and safety: AI systems should be robust, secure and safe throughout the entire lifecycle to prevent misuse and mistakes.
5. Accountability: AI developers should be accountable for the functionality and repercussions of the AI systems they build.

NIST AI Risk Management Framework

Highlighting risks across AI lifecycles and the qualities of trustworthy AI systems, the NIST AI Risk Management Framework was published in January 2023. The voluntary framework recommends testing, evaluation, verification and validation tasks. It also points to human judgment as a guide for trustworthiness metrics. 

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