Key Insights:
- 48% of employees fear unethical AI use, underscoring the urgent need for responsible oversight.
- AI ethics focus on fairness, transparency, and protecting human values from bias and harm.
- Real-world cases reveal AI’s tendency to reinforce bias and make flawed, high-impact decisions.
- Responsible AI requires accountability, explainability, and human oversight at every stage.
- Bias, privacy risks, and lack of transparency remain the top ethical threats in AI.
- AI’s heavy energy use raises sustainability and environmental concerns.
- Copyright disputes, like Getty Images vs. Stability AI, are shaping future AI regulations.
- Legal and moral debates continue over AI authorship, accountability, and potential rights.
- The London Blockchain Conference 2025 on 22-23 October will explore these key AI ethics and issues.
There’s been an increasing focus on the ethics of AI since the launch of tools like ChatGPT in 2022. The level of concern has been highlighted by an Institute of Business Ethics survey, revealing that 48% of employees fear the misuse of AI for unethical reasons.
From the legal complications associated with copyright infringement to the potential for excessive energy use, we focus on the key ethical concerns. Read on as we explain the meaning of responsible AI and the core issues that must be addressed for greater confidence in AI.
Defining the Ethics of AI
First of all, it’s worth explaining exactly what we mean by the ethics of AI. This relates to the principles that shape AI’s behaviour in terms of human values. The prioritisation of AI ethics can make a difference in reducing the risk of bias, breaking down barriers to accessibility, supporting human creativity, and ensuring other societal benefits.
From the calculation of mortgage interest rates to the evaluation of university applications, AI is being used for various decision-making purposes. There’s a perception that the AI will make ethically sound decisions, given the avoidance of human bias. However, there are numerous cases that call such ethical trust into question.
Here are some examples:
- The use of AI algorithms based on historical data, resulting in the overpolicing of people of colour
- The incorrect diagnoses of patient health issues (as with the Watson for Oncology tool)
- Students using AI for “writing” essays and papers that mimic original work
These instances have led to the prioritisation of AI ethics, with McKinsey predicting that such initiatives will grow to a value in excess of $10 billion in 2025.
What is Responsible AI?
From logistics planning to investment decisions evaluation, the range of AI applications continues to grow. As such, it’s vital for AI tools to be developed with an understanding of potential issues, limitations, and unintended consequences.
While there’s no standard definition of responsible AI, organisations are expected to take accountability in line with their missions and values. There should be defined and repeatable processes for the development and deployment of AI.
Core Principles in the Ethics of AI
These five principles underlie the responsible use of AI:
- Fairness – There should be confidence in the fairness of AI-generated results (particularly in relation to historically underrepresented groups).
- Explainability – There should be clarity on how datasets are used to train AI models.
- Robustness – There should be minimal risk of AI systems being hacked for the benefit of particular groups.
- Transparency – There should be open communication over the use of AI models, including sharing as much information as possible with end users.
- Data privacy – There should be assurances over the security of any data that is entered and generated by AI systems.
The well-being, safety, and dignity of individuals should be prioritised in any decisions regarding the development and use of AI. There should be minimal to no risk of such systems either replacing people or compromising human welfare. Human oversight is also vital, ensuring the avoidance of bias and discrimination in the use of AI tools.
Core Ethical Issues in AI
As mentioned, AI is associated with various ethical concerns. Such systems have come under particular scrutiny due to their perpetuation of biases, which, if unchecked, may lead to discrimination and social harm. Organisations are encouraged to minimise such risks through the implementation of bias audits and verification of the AI-generated results.
The black box nature of AI systems has also been criticised, with people seeking greater transparency as such technologies are used to inform increasingly impactful decisions. This has led to the development of new techniques for the analysis of AI-generated results and confirmation of model behaviour. Regulations have also been introduced, with a focus on ensuring explainability.
Data privacy is another key issue, with concerns over the use of personal information, surveillance, and the safeguarding of AI results. Such concerns are being addressed through techniques such as differential privacy and measures to protect individual data.
The everyday use of AI technologies is also placing some strain on environmental resources. On one hand, there’s an increasing demand for high-capacity data centres with high levels of energy consumption to enable the development and training of new models. On the other hand, such advanced models may be used to make better-informed decisions for carbon footprint reduction.
AI and Copyright
There’s clear potential for harm, given the risks of AI generating incorrect “hallucinations” and results that perpetuate established biases. The technology has also been criticised for copying human creators, with no option for opting out or giving consent for the inclusion of original and modified works in the AI results. Such unethical AI practices could slow the pace of development and adoption.
The copyright issue is subject to ongoing debate, with questions over whether the AI results represent the digital version of human learning or the collation of data from original sources. This is reflected in the case of Getty Images vs Stability AI, which claimed that the AI images have been modelled on commercially available originals. Decisions in such cases could have a direct bearing on the future of AI.
Other AI Legalities
Given the copyright concerns, you may wonder – is AI legal? The answer is multifaceted. While popular platforms such as ChatGPT and Perplexity are entirely legal, specific regulations apply to the use of AI-generated content. It’s generally best to exercise caution and not attempt to pass such results off as your own work.
Another key question is, should AI have rights? Again, the answer is some way from straightforward, given the rapid development of AI technologies. There may come a time when we move beyond the complete control of AI systems to the granting of some freedom and autonomy. The issue of independent rights will be a key issue as more advanced forms of AI are developed.
Discover More at the London Blockchain Conference
Set for the 22nd and 23rd of October, the London Blockchain Conference will provide the opportunity to learn more about such key AI debates and trends. With expert insights into everything from digital trust to secure systems design, this conference will point the way to a digital future that we can trust.
Register for your tickets and join the leaders shaping tomorrow.
