Ethical AI: Implications for developers and consumers

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  Quantumrun Foresight
• April 28, 2022

Insight summary

The rise of ethical AI, or roboethics, is shaping the way humans build and interact with artificial intelligence systems, emphasizing moral standards and socially acceptable behaviors. This movement is driving changes across various sectors, from creating new job opportunities and legal challenges to influencing government policies and consumer behavior. The long-term implications of ethical AI affect social norms, business models, international relations, and environmental sustainability.

Ethical AI context

Ethical AI, sometimes called roboethics, refers to how humans conduct themselves when building artificial intelligence systems and the moral standards they apply to the AI systems they develop. Ethical AI further encompasses the idea of how AI will behave and the expectation that such behaviors will be socially and morally acceptable. The purpose of ethical AI is to guide the AI community to answer the questions of if, when, why, and how when designing, building, using, protecting, and managing AI systems.

Critical to this endeavor is leveraging the guidelines contained in a structured AI ethics framework. The ethics framework is also meant to aid with the implementation of these guidelines by the stakeholders involved. In addition, the framework should support and drive an organizational culture where data and an AI ethics strategy can be successfully deployed and maintained; this requires educating and upskilling all employees involved in the development of AI systems. 

The tenets of AI ethics entail that the development and use of AI should be transparent, secure, resilient, be fundamentally informed by science and technology, and be built to meet end-user expectations. Automated actions by AI systems should be justifiable and explicable concerning human rights, dignity, and freedom. Ultimately, ethical AI entails that AI or its use does not cause harm to people. 

Disruptive impact

Research consulted by the Pew Research Center and Elon University revealed that the full breadth of ethical AI standards may not be achievable even by 2030. According to this research, the development of AI will still revolve around generating profit throughout the 2020s. Stakeholders in AI-producing industries are reportedly more concerned about maintaining social control than reaching a consensus on how to devise and implement ethical AI strategies in their products and systems.

While companies are likely to continue prioritizing profitability, they could also consider introducing ethical AI manifestos to guide their AI initiatives as it is paramount to the sustainability of the industry at large. For developers, ethical AI would mean that they find a balance between the technicalities of building AI-powered applications and foreseeing and compensating for the possible implications of those applications within different ethical contexts.

If ethical AI becomes more widely accepted, it could lead to a higher level of trust in automated systems. This trust may encourage people to embrace these systems in areas and situations where they might have been previously hesitant or opposed. The growth in the use of automation and AI systems could also result in changes within the workforce, particularly in industries where these technologies can be applied, altering traditional roles and possibly creating new opportunities.

Implications of ethical AI

Wider implications of ethical AI may include: 

• Companies being vulnerable to legal risks due to intended or unintended unethical AI practices, leading to a heightened need for compliance and monitoring mechanisms within organizations.


• New opportunities in the job market as large technology companies within the AI sector employ experts to analyze data and plan for possible ethical problems and dilemmas, fostering a new specialty within the technology field.


• Establishment of government policies and regulatory bodies to control the advancement of AI and support the relationship between companies, how companies use AI, and consumers, ensuring a balanced approach that protects individual rights while allowing for technological progress.


• The creation of a standard set of AI ethics principles that all AI developers and manufacturers are obliged to include in their AI programming and design, leading to a more uniform and transparent approach to ethical considerations in AI development.


• A shift in consumer behavior towards products and services that adhere to ethical AI principles, leading to a more conscious and responsible consumption pattern.


• The retraining and education of existing workforce members in industries heavily reliant on AI, leading to a more skilled and adaptable labor market.


• An increased focus on environmental sustainability in AI development and deployment, leading to more energy-efficient algorithms and reduced electronic waste.


• The emergence of new business models that prioritize ethical considerations in AI, leading to a shift in competitive dynamics and market positioning.


• The potential for international collaboration or conflict over ethical AI standards and regulations, leading to a complex geopolitical landscape that could shape global trade and diplomacy.

Questions to consider

• How important is it for the companies that develop AI systems to incorporate ethics into their AI systems, programs, employee policies, and work processes as these tools are produced?


• What steps can companies take to tackle public skepticism towards themselves and the ethical challenges and problems posed by AI systems?