In the ever-evolving landscape of technology, artificial intelligence (AI) has emerged as a double-edged sword, wielding immense power to transform industries and human lives while posing ethical and accountability challenges.
AI's meteoric rise in recent years means chatbots now assist customer support daily and autonomous vehicles navigate streets. The tech has infiltrated various domains, revolutionising the way we work, play, and interact with the world. But as its reach extends, so do ethical concerns.
Now, with the announcement of Elon Musk’s “spicy” AI bot, Grok, and the use of AI to steal Scarlett Johansson’s voice, we’re diving into the ethical considerations surrounding AI development and deployment.
There’s lots to think about as we proceed into an inevitable AI-driven future. From bias in algorithms to privacy concerns, and the responsibility of tech companies to ensure ethical practices.
Ensuring transparency
The first challenge in AI ethics is transparency. When AI systems make decisions that impact our lives, it's crucial – and increasingly difficult – to understand how those decisions are made. But a lack of transparency can lead to mistrust and unintended consequences.
It might seem strange that even creators of an AI can't understand its thinking process, but in many ways that’s how human thinking processes sometimes work, too. And it's this same feature that underpins its success: AI is a self-training tool that can perform calculations beyond the ability of humans.
It’s part of the reason some have called for a “right to explanation” when it comes to the use of AI. Researchers and developers are turning to Explainable AI (XAI), a field that focuses on making AI systems more transparent and understandable. Routledge and Tae Wan Kim’s analysis on the right to explanation argues that the public has an ethical right to know how AI models make decisions – and that they should even be held to a similar standard as medicine.
By providing insights into the decision-making process, XAI not only boosts accountability but can help users trust AI-powered systems.
Avoiding bias
Right to explanation can also be useful when it comes to understanding bias in AI systems. AI algorithms can inherit biases from the data they are trained on, which can lead to discriminatory outcomes – so having insight into how the AI has reached that conclusion is crucial.
A notorious example was Amazon's recruitment tool, which was scrapped after favouring male candidates over female ones. AI systems should be designed and trained with diversity and fairness in mind, with continuous monitoring to detect and rectify biases.
In the pursuit of addressing these challenges, organisations are setting up AI ethics boards and committees. Google even established an AI Ethics Board established in 2019, aiming to provide guidelines and oversight for ethical AI development at DeepMind. But the board was disbanded just two weeks after its inception, illustrating the complexity of navigating the AI ethics landscape.
Who’s accountable?
Accountability, meanwhile, poses as many challenges as ethics. Who’s responsible when AI systems make mistakes or harm individuals: The developers, the organisations deploying AI, or the AI itself?
These questions are far from straightforward. One case study that exemplifies the struggle with AI accountability is the Uber self-driving car accident in 2018. An autonomous Uber vehicle struck and killed a pedestrian in Arizona. The incident raised questions about the accountability of both Uber and the safety driver in the vehicle, and after lengthy legal proceedings, the human backup driver was ultimately held responsibly.
As AI systems become more integrated into our lives, establishing a framework for assigning accountability is imperative.
Privacy concerns
According to a new study by researchers at ETH Zurich, as AI gets smarter, it can begin to "infer personal data at a previously unattainable scale" with dangerous consequences – for example being used by hackers.
"The key observation of our work is that the best LLMs are almost as accurate as humans, while being at least 100x faster and 240x cheaper in inferring such personal information," said Mislav Balunovic, a PhD student at ETH Zurich and one of the authors of the study.
"Individual users, or basically anybody who leaves textual traces on the internet, should be more concerned as malicious actors could abuse the models to infer their private information."
Deepfakes and facial recognition
On top of this, powerful facial recognition software has sprung up, driven by deep learning algorithms – and enabling anyone to create convincing deepfake photos and videos in a matter of minutes.
As Hollywood actors and writers reach a tentative deal to end their strikes in the face of the growing creative threat from AI, future solutions need to protect creators and public figures from being digitally copied without their consent.
Beyond the world of entertainment, even more serious questions are being asked about how AI could be used, as London’s Metropolitan Police force expand facial recognition tech - fuelling concerns grow about how easily it could be used to curtail freedoms.
Government responsibility
As such, it's not just corporations and developers who shoulder the responsibility. Governments and international organisations play a vital role in shaping AI ethics and accountability.
The UN has established a High-Level Advisory Body on artificial intelligence. Bringing together up to 38 experts in relevant disciplines from around the world, the Body will offer diverse perspectives and options on how AI can be governed for the common good, aligning internationally interoperable governance with human rights and the Sustainable Development Goals.
In the UK, Prime Minister Sunak has established an AI Safety Institute – but to become effective and more than just a political play, it needs to be rigorously overseen. The institute aims to evaluate and test various AI models to understand their capabilities, including addressing issues related to bias, misinformation, and more extreme threats.
The UK government has also set out a 7-point framework to try to address questions of ethics and accountability:
1. Test to avoid any unintended outcomes or consequences
2. Deliver fair services for all of our users and citizens
3. Be clear who is responsible
4. Handle data safely and protect citizens’ interests
5. Help users and citizens understand how it impacts them
6. Ensure that you are compliant with the law
7. Build something that is future proof
VR’s role in AI ethics
Does other technology have a role in establishing an ethical framework for artificial intelligence? VR is playing its own role in addressing AI ethics and accountability, with virtual simulations helping to train AI systems to better understand human behaviours and nuances - thereby reducing the likelihood of biased or unfair decisions.
One fascinating development in this regard is the use of VR to simulate real-world scenarios and train AI systems to react appropriately. For instance, AI systems that assist in medical diagnosis can benefit from VR simulations that replicate patient interactions. This not only improves their accuracy but also ensures that AI understands the intricacies of human communication and empathy. But does this also mean the AI holds a share of the accountability?
Additionally, VR can be instrumental in creating immersive scenarios for AI ethics training. By placing individuals in scenarios where ethical decisions must be made, VR can help build empathy and awareness around AI's impact on society.
Organisational initiatives
As we navigate the uncharted waters of AI ethics and accountability, it's crucial to stay informed about the latest research and best practices. Initiatives like the Partnership on AI and organizations like OpenAI are dedicated to advancing responsible AI development.
Moreover, public engagement is vital in shaping the future of AI ethics. Brands like Microsoft have sought public input on AI policies and have established external ethics advisory boards to ensure diverse perspectives are considered.
The future is artificial
The path to navigating the challenges of AI ethics and accountability is both exhilarating and treacherous. The power of AI to transform our world is undeniable, but transparency, fairness, and accountability must be at the forefront of development. Innovative solutions like Explainable AI and VR simulations can help us pave the way.
To mitigate ethical challenges and ensure accountability, continuous research and innovation are essential too. AI researchers are exploring techniques like adversarial training, which helps reduce bias in AI systems, and reinforcement learning from human feedback, which enables AI to learn from human input and improve its decision-making.
Ultimately, it's a collaborative effort that involves technology experts, organisations, governments, and the public to ensure that AI remains a force for good, enhancing our lives while upholding the highest ethical standards. As we continue on this journey, we must remember that the choices we make today will shape the future of AI and, by extension, the world we live in.
