Smartwatches transforming health monitoring

Smartwatches are revolutionising preventative health by providing continuous, detailed insights into users’ physiological data. At CHUV University Hospital, Chief Anaesthesiologist Patrick Schoettker is exploring ways to leverage smartwatches like the Masimo W1 to monitor patients ahead of surgery. This device collects real-time health data, including heart rate, oxygen levels, and hydration, to create a “digital twin” that could help identify and mitigate risks before operations. Schoettker and his team hope to reduce surgery-related complications by using these insights to anticipate issues.

The potential of smartwatches extends beyond surgery. Leading cardiologists, like Gosia Wamil at Mayo Clinic Healthcare, are already using smartwatch data to detect irregular heart rhythms and other cardiac conditions early, facilitating timely intervention. AI algorithms can now analyse data from wearable devices to predict more serious heart issues, such as low ejection fraction—an early warning sign of heart failure. This technology has also proven useful in tracking health risks among patients with chronic conditions like diabetes, to prevent complications such as heart attacks and strokes.

Beyond cardiology, wearable technology holds promise for neurological and chronic conditions. Research has shown that smartwatches can detect early signs of Parkinson’s disease years before symptoms are noticed by patients. Studies are also underway to assess how smartwatch data might predict seizures in epilepsy patients, helping them better manage risks. As smartwatches grow more sophisticated, their ability to track various health metrics could reshape preventative care. While concerns about false positives remain, experts believe the benefits, such as early detection and reduced healthcare costs, are likely to outweigh these challenges.

AI at Europe’s borders sparks human rights concerns

As the European Union implements the world’s first comprehensive regulations on artificial intelligence (AI), human rights groups are raising alarms over exemptions for AI use at Europe’s borders. The EU’s AI Act, which categorises AI systems by risk level and imposes stricter rules for those with higher potential for harm, is set to take full effect by February 2025. While it promises to regulate AI across industries, controversial technologies like facial and emotion recognition are still permitted for border and police authorities, sparking concern over surveillance and discrimination.

With Europe investing heavily in border security, deploying AI-driven watchtowers and algorithms to monitor migration flows, critics argue these technologies could criminalise migrants and violate their rights. Human Rights activists warn that AI may reinforce biases and lead to unlawful pushbacks of asylum seekers. Countries like Greece are testing ground for these technologies and have been accused of using AI for surveillance and discrimination, despite denials from the government.

Campaigners also point out that the EU’s regulations allow European companies to develop and export harmful AI systems abroad, potentially fueling human rights abuses in other countries. While the AI Act represents a step forward in global regulation, activists believe it falls short of protecting vulnerable groups at Europe’s borders and beyond. They anticipate that legal challenges and public opposition will eventually close these regulatory gaps.

AI and ethics in modern society

Humanity’s rapid advancements in robotics and AI have shifted many ethical and philosophical dilemmas from the realm of science fiction into pressing real-world issues. AI technologies now permeate areas such as medicine, public governance, and the economy, making it critical to ensure their ethical use. Multiple actors, including governments, multinational corporations, international organisations, and individual citizens, share the responsibility to navigate these developments thoughtfully.

What is ethics?

Ethics refers to the moral principles that guide individual behaviour or the conduct of activities, determining what is considered right or wrong. In AI, ethics ensures that technologies are developed and used in ways that respect societal values, human dignity, and fairness. For example, one ethical principle is respect for others, which means ensuring that AI systems respect the rights and privacy of individuals.

What is AI?

Artificial Intelligence (AI) refers to systems that analyse their environment and make decisions autonomously to achieve specific goals. These systems can be software-based, like voice assistants and facial recognition software, or hardware-based, such as robots, drones, and autonomous cars. AI has the potential to reshape society profoundly. Without an ethical framework, AI could perpetuate inequalities, reduce accountability, and pose risks to privacy, security, and human autonomy. Embedding ethics in the design, regulation, and use of AI is essential to ensuring that this technology advances in a way that promotes fairness, responsibility, and respect for human rights.

AI ethics and its importance

AI ethics focuses on minimising risks related to poor design, inappropriate applications, and misuse of AI. Problems such as surveillance without consent and the weaponisation of AI have already emerged. This calls for ethical guidelines that protect individual rights and ensure that AI benefits society as a whole.

a person in a white suit

Global and regional efforts to regulate AI ethics

There are international initiatives to regulate AI ethically. For example, UNESCO‘s 2021 Recommendation on the Ethics of AI offers guidelines for countries to develop AI responsibly, focusing on human rights, inclusion, and transparency. The European Union’s AI Act is another pioneering legislative effort, which categorises AI systems by their risk level. The higher the risk, the stricter the regulatory requirements.

The Collingridge dilemma and AI

The Collingridge dilemma points to the challenge of regulating new technologies like AI. Early regulation is difficult due to limited knowledge of the technology’s long-term effects, but once the technology becomes entrenched, regulation faces opposition from stakeholders. AI is currently in a dual phase: while its long-term implications are uncertain, we already have enough examples of its immediate impact—such as algorithmic bias and privacy violations—to justify regulation in key areas.

Asimov’s Three Laws of Robotics: Ethical inspiration for AI

Isaac Asimov’s Three Laws of Robotics, while fictional, resonate with many of the ethical concerns that modern AI systems face today. These laws—designed to prevent harm to humans, ensure obedience to human commands, and prioritise the self-preservation of robots—provide a foundational, if simplistic, framework for responsible AI behaviour.

 Page, Text, Chart, Plot

Modern ethical challenges in AI

However, real-world AI introduces a range of complex challenges that cannot be adequately managed by simple rules. Issues such as algorithmic bias, privacy violations, accountability in decision-making, and unintended consequences complicate the ethical landscape, necessitating more nuanced and adaptive strategies for effectively governing AI systems.

As AI continues to develop, it raises new ethical dilemmas, including the need for transparency in decision-making, accountability in cases of accidents, and the possibility of AI systems acting in ways that conflict with their initial programming. Additionally, there are deeper questions regarding whether AI systems should have the capacity for moral reasoning and how their autonomy might conflict with human values.

Categorising AI and ethics

Modern AI systems exhibit a spectrum of ethical complexities that reflect their varying capabilities and applications. Basic AI operates by executing tasks based purely on algorithms and pre-programmed instructions, devoid of any moral reasoning or ethical considerations. These systems may efficiently sort data, recognise patterns, or automate simple processes, yet they do not engage in any form of ethical deliberation.

In contrast, more advanced AI systems are designed to incorporate limited ethical decision-making. These systems are increasingly being deployed in critical areas such as healthcare, where they help diagnose diseases, recommend treatments, and manage patient care. Similarly, in autonomous vehicles, AI must navigate complex moral scenarios, such as how to prioritise the safety of passengers versus pedestrians in unavoidable accident situations. While these advanced systems can make decisions that involve some level of ethical consideration, their ability to fully grasp and navigate complex moral landscapes remains constrained.

The variety of ethical dilemmas

 Logo, Nature, Outdoors, Person

Legal impacts

The question of AI accountability is increasingly relevant in our technologically driven society, particularly in scenarios involving autonomous vehicles, where determining liability in the event of an accident is fraught with complications. For instance, if an autonomous car is involved in a collision, should the manufacturer, software developer, or vehicle owner be held responsible? As AI systems become more autonomous, existing legal frameworks may struggle to keep pace with these advancements, leading to legal grey areas that can result in injustices. Additionally, AI technologies are vulnerable to misuse for criminal activities, such as identity theft, fraud, or cyberattacks. This underscores the urgent need for comprehensive legal reforms that not only address accountability issues but also develop robust regulations to mitigate the potential for abuse.

Financial impacts

The integration of AI into financial markets introduces significant risks, including the potential for market manipulation and exacerbation of financial inequalities. For instance, algorithms designed to optimise trading strategies may inadvertently favour wealthy investors, perpetuating a cycle of inequality. Furthermore, biased decision-making algorithms can lead to unfair lending practices or discriminatory hiring processes, limiting opportunities for marginalised groups. As AI continues to shape financial systems, it is crucial to implement safeguards and oversight mechanisms that promote fairness and equitable access to financial resources.

Environmental impacts

The environmental implications of AI cannot be overlooked, particularly given the substantial energy consumption associated with training and deploying large AI models. The computational power required for these processes contributes significantly to carbon emissions, raising concerns about the sustainability of AI technologies. In addition, the rapid expansion of AI applications in various industries may lead to increased electronic waste, as outdated hardware is discarded in favour of more advanced systems. To address these challenges, stakeholders must prioritise the development of energy-efficient algorithms and sustainable practices that minimise the ecological footprint of AI technologies.

Social impacts

AI-driven automation poses a profound threat to traditional job markets, particularly in sectors that rely heavily on routine tasks, such as manufacturing and customer service. As machines become capable of performing these jobs more efficiently, human workers may face displacement, leading to economic instability and social unrest. Moreover, the deployment of biassed algorithms can deepen existing social inequalities, especially when applied in sensitive areas like hiring, loan approvals, or criminal justice. The use of AI in surveillance systems also raises significant privacy concerns, as individuals may be monitored without their consent, leading to a chilling effect on free expression and civil liberties.

Psychological impacts

The interaction between humans and AI systems can have far-reaching implications for emotional well-being. For example, AI-driven customer service chatbots may struggle to provide the empathetic responses that human agents can offer, leading to frustration among users. Additionally, emotionally manipulative AI applications in marketing may exploit psychological vulnerabilities, promoting unhealthy consumer behaviours or contributing to feelings of inadequacy. As AI systems become more integrated into everyday life, understanding and mitigating their psychological effects will be essential for promoting healthy human-computer interactions.

Trust issues

Public mistrust of AI technologies is a significant barrier to their widespread adoption. This mistrust is largely rooted in the opacity of AI systems and the potential for algorithmic bias, which can lead to unjust outcomes. To foster trust, it is crucial to establish transparent practices and accountability measures that ensure AI systems operate fairly and ethically. This can include the development of explainable AI, which allows users to understand how decisions are made, as well as the implementation of regulatory frameworks that promote responsible AI development. By addressing these trust issues, stakeholders can work toward creating a more equitable and trustworthy AI landscape.

These complex ethical challenges require global coordination and thoughtful, adaptable regulation to ensure that AI serves humanity’s best interests, respects human dignity, and promotes fairness across all sectors of society. The ethical considerations around AI extend far beyond individual technologies or industries, impacting fundamental human rights, economic equality, environmental sustainability, and societal trust.

As AI continues to advance, the collective responsibility of governments, corporations, and individuals is to build robust, transparent systems that not only push the boundaries of innovation but also safeguard society. Only through an ethical framework can AI fulfil its potential as a transformative force for good rather than deepening existing divides or creating new dangers. The journey towards creating ethically aware AI systems necessitates ongoing research, interdisciplinary collaboration, and a commitment to prioritising human well-being in all technological advancements.