Ensuring AI Takes Actions for a Better Human Life in the Future

Artificial intelligence (AI) is rapidly becoming a part of everyday life, from healthcare to transportation and education. Yet, a pressing question remains: how can we be sure that AI will act in ways that improve human life rather than cause harm or deepen inequalities? This concern is not just about technology but about the values and systems guiding AI development and deployment. Understanding how to ensure AI benefits humanity requires looking at the design, governance, and ethical frameworks shaping its future.

AI-driven urban transportation system

Building AI with Human-Centered Values

The foundation for AI that supports better human life lies in embedding human values into its design. This means developers and organizations must prioritize:

• Safety: AI systems should avoid causing physical or psychological harm. For example, autonomous cars must be programmed to minimize accidents and protect pedestrians.

• Fairness: AI should not reinforce biases or discrimination. Algorithms used in hiring or lending must be tested to prevent unfair treatment of any group.

• Transparency: People should understand how AI decisions are made. Clear explanations help users trust and challenge AI outcomes when necessary.

• Privacy: AI must respect personal data and avoid intrusive surveillance without consent.

  
  

A practical example is the development of AI in healthcare. Systems that assist doctors in diagnosing diseases must be rigorously tested to ensure accuracy across diverse populations. They should also provide clear reasons for their recommendations, allowing doctors to make informed decisions.

Governance and Regulation to Guide AI Development

Technology alone cannot guarantee positive outcomes. Governments, international bodies, and industry groups play a crucial role in setting rules and standards for AI. Effective governance includes:

• Creating ethical guidelines: Many organizations have published AI ethics principles, such as the European Commission’s Ethics Guidelines for Trustworthy AI. These provide a framework for responsible AI use.

• Enforcing accountability: Companies and developers should be held responsible for the impacts of their AI systems. This includes mechanisms for redress if AI causes harm.

• Promoting collaboration: Sharing knowledge and best practices across countries and sectors helps avoid harmful AI applications and encourages beneficial innovations.

  
  

For instance, the General Data Protection Regulation (GDPR) in Europe sets strict rules on data use that affect AI systems, ensuring users have control over their information. Such regulations help align AI development with societal values.

Robotic arm assisting in surgery

Encouraging Public Engagement and Education

People must be part of the conversation about AI’s role in society. Public engagement helps identify concerns, values, and priorities that might be overlooked by technologists. This can happen through:

• Community forums and consultations: Allowing diverse voices to influence AI policies and projects.

• Educational programs: Teaching people about AI’s capabilities and limitations empowers them to make informed choices and advocate for their interests.

• Transparency in AI use: Organizations should openly communicate when and how AI is used, especially in sensitive areas like law enforcement or social services.

  
  

An example is the use of AI in criminal justice. Public debate and oversight are essential to prevent biased algorithms from unfairly targeting certain groups. When communities understand AI’s role, they can push for fairer systems.

Students learning about AI in classroom

Continuous Monitoring and Improvement

AI systems must be regularly reviewed and updated to respond to new challenges and feedback. This includes:

• Auditing algorithms: Independent audits can detect biases or errors that developers missed.

• Monitoring real-world impacts: Tracking how AI affects people’s lives helps identify unintended consequences.

• Adapting to change: AI should evolve as society’s needs and values shift, ensuring ongoing alignment with human well-being.

  
  

For example, facial recognition technology has faced criticism for racial bias. Some cities have banned or limited its use until better safeguards are in place. This shows the importance of monitoring AI after deployment.