Artificial Intelligence (AI) is transforming industries and impacting society in ways that may not be fully recognized. In the healthcare industry, AI is leveraged to conduct complex diagnoses, reviewing MRIs, CT scans and mammograms to detect cancer with greater accuracy. AI has also reshaped the way that society interacts with its smart devices—from virtual assistants like Siri and Alexa to smart security features such as facial recognition. However, as AI continues to transform society, it raises serious ethical challenges. Of critical concern is algorithmic parity: are AI systems unintentionally perpetuating biases? Additionally, who is accountable when AI makes a wrong decision? Addressing these concerns is an essential undertaking for organizations, policymakers, and society to ensure that AI systems are trustworthy and aligned with societal values.
While everyone may have their own definition of ethics or ethical, EAI is a bit more focused. The faculty.ai defines ethical AI as follows:
Ethical AI is when AI systems are designed and deployed in ways that consider the harms associated with AI systems and [have] mitigated them. These harms include bias and discrimination, unsafe or unreliable outcomes, unexplainable outcomes and invasions of privacy.
Since AI’s use is pervasive in critical industries such as healthcare, finance, and public services, ethical considerations are essential to its design because of AI’s ability to impact individuals on a personal level. For example, Amazon’s hiring algorithm was found to discriminate against female applicants because it was trained on resumes which were submitted over a decade ago and these applicants, were primarily male. Without clear ethical guidelines in place, the use of AI can unintentionally introduce biases in decision-making such as those evidenced in Amazon’s recruiting process.
Since AI is evolving at a pace that is hard for laws and regulations to keep up with, there can be accountability challenges when mistakes are made. Including ethics into AI from the design phase subverts this risk, allowing the technology to work for everyone in a fair, transparent, and responsible manner.
The EU Artificial Intelligence Act, a key legislation aimed at comprehensively regulating AI was passed in August 2024 to address many of the ethical concerns associated with AI’s use. This act categorizes AI systems into three risk-based categories:
In addition to the EU Artificial Intelligence Act, the NIST AI Risk Management Framework (AI RMF) is a commonly referenced framework that provides AI ethics guidelines. This framework highlights four pillars for managing AI-related risks:
Organizations can ensure that their AI technology includes ethical considerations by using these strategies:
Since AI systems require a lot of data to work well, it raises privacy concerns. How do organizations strike a balance between using data to power AI and protecting people’s privacy? Best practices include:
As AI becomes more ingrained in organizational processes, ensuring accountability is critical. Companies should establish governance bodies such as an AI ethics board that can actively manage and monitor AI development and deployment. Additionally, organizations should also keep up with proposed legislation such as the Algorithmic Accountability Act that urges organizations to assess the impact of their AI technologies to facilitate transparency and fairness in AI outcomes.
While the challenges of AI ethics are complex, it also provides an opportunity to guide the future of technology in a way that reflects societal values. Organizations and policymakers should work together to develop guidelines and regulations that ensure that AI is used ethically.
Although AI has already delivered on its potential to improve society, it is crucial that it is managed and monitored from development to deployment so that it is equally beneficial. By focusing on fairness, transparency, and accountability, an AI-driven future can be created that works for everyone.
As AI becomes a key strategy in business operations, it is essential to ensure that both its ethical and security aspects are managed effectively. At ROCIMG, we help clients navigate these challenges by developing AI policies, and developing data governance best practices that align with the latest security standards. Our commitment to ethical AI reflects our vision for a future where AI technology aligns with societal values.
With 3+ years in cybersecurity consulting, Abigail brings unparalleled expertise in risk management, vulnerability, assessments, and strategic security planning. She is adept at both active and reactive security measures, excelling in performing cybersecurity risk assessments and audits against industry-standard frameworks, developing robust security policies and procedures, conducting vulnerability and penetration assessments, and developing remediation roadmaps.
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