Seven ethical considerations in AI: building a responsible future

In mid-November 2024, Campbell Tickell and the Disruptive Innovator’s Network ran a webinar for the launch of their joint report: AI in Social Housing Building on her contribution in the webinar, Joanna Sedley-Burke, Campbell Tickell Associate and contributor to the report, discusses seven ethical considerations of using AI.  

 

Artificial Intelligence (AI) is no longer a distant concept; it is a transformative force reshaping industries, economies, and societies, social housing is part of thisAs its integration deepens, the ethical considerations surrounding AI become critical. To ensure AI development aligns with human values, we must tackle key issues, including bias, privacy, accountability, and societal impact. So here is my take on a healthy approach to the introduction of AI.

Bias and fairness

AI systems are only as unbiased as the data they learn from. Unfortunately, datasets often reflect historical prejudices or societal inequalities, leading to discriminatory outcomes. For instance, biased AI can influence hiring processes, criminal justice, or loan approvals, disproportionately affecting marginalised groups. Ethical AI requires meticulous data curation, ongoing algorithm audits, and the inclusion of diverse voices in development. Developers must aim for fairness by identifying and mitigating biases at every stage of AI deployment, ensuring technology promotes equity rather than perpetuating discrimination. 

Privacy, transparency, and explainability

AI systems often rely on vast amounts of personal data, raising serious privacy concerns. Users have the right to understand how their data is collected, processed, and used. Transparency ensures accountability and builds trust between AI systems and their users. Additionally, explainability—making AI decisions understandable—is essential, especially in sensitive areas like healthcare or law. By demystifying AI decision-making, individuals can question outcomes, ensuring that the technology operates ethically and fairly. Developers and organisations must adopt transparent practices and prioritise user privacy to foster trust and protect individual rights. 

Accountability

When AI systems make mistakes or cause harm, who is responsible? This question underpins the need for clear accountability frameworks. Without such structures, affected parties may struggle to find recourse. Developers, organisations, and policymakers must establish standards that delineate responsibility for AI-driven outcomes. For example, if a self-driving car causes an accident, accountability must be clearly assigned, whether to the manufacturer, the software developer, or the operator. Ethical AI requires a proactive approach to defining and upholding accountability at every level. 

Autonomy and human control

While AI can automate tasks and make decisions, ethical development ensures it does not undermine human autonomy. In critical areas like social housing, healthcare, defence, or finance, human oversight is vital. AI should function as a tool to enhance decision-making rather than replace it entirely. Striking a balance between automation and human control preserves ethical standards and safeguards against unintended consequences. Developers must prioritise human-in-the-loop systems that maintain accountability and ensure AI aligns with societal values. 

Job displacement and economic impact

AI-driven automation poses significant economic challenges, including the potential displacement of jobs. While AI creates opportunities in emerging fields, it also risks widening economic inequalities, especially for workers in repetitive or low-skill roles. Governments and businesses have an ethical obligation to support affected workers through reskilling initiatives, education programs, and economic policies that promote equitable growth. Preparing the workforce for an AI-driven future ensures that the benefits of this technology are distributed fairly, fostering economic stability and inclusion. 

Security and safety

As AI becomes more advanced, its misuse becomes a critical concern. From deepfakes to autonomous weaponry, the potential for harm is significant. Ensuring the security and safety of AI systems requires rigorous testing, robust cybersecurity measures, and ethical safeguards. Developers must anticipate potential risks and implement strategies to prevent exploitation. Ethical AI development also involves ensuring systems are resilient to failures, protecting both users and broader society from unintended consequences. 

Long-term societal impact

The long-term implications of AI on society extend beyond immediate applications. From influencing cultural norms to shaping global power dynamics, AI has the potential to redefine human interaction and progress. Ethical AI development must prioritise sustainability, inclusivity, and societal well-being. Policymakers, businesses, and communities must collaborate to ensure that AI benefits future generations. This involves fostering interdisciplinary dialogue, considering environmental impacts, and addressing disparities in AI access and usage. 

Conclusion

As AI continues to evolve, embedding ethics into its development and deployment is no longer optional—it is imperative. Addressing concerns like bias, privacy, accountability, and societal impact ensures AI becomes a tool for positive change. By prioritising ethical considerations, we can harness AI’s transformative power responsibly, creating a future where technology serves humanity, safeguards equity, and upholds shared values. Together, we must navigate the challenges of AI to ensure its promise is realised without compromising our principles.  

Further resources 

To discuss any issues raised in this article email: comms@campbelltickell.com 

Seven ethical considerations in AI: building a responsible future

Campbell Tickell is extremely proud to announce that it is has been certified as a B Corporation. Verified by B Lab, certified B Corporations (or B Corps) are companies that meet high standards of social and environmental performance, transparency, and accountability.

[stm_about_vacancy css=".vc_custom_1453112586637{margin-bottom: 60px !important;}"]