Teams designing AI should include linguistics and philosophy experts, parents, young people, everyday people with different life experiences from different socio-economic backgrounds.
Category: ethics – Page 3
• Ethics: As AI gets more powerful, we need to address ethics such as bias in algorithms, misuse, privacy and civil liberties.
• AI Regulation: Governments and organizations will need to develop regulations and guidelines for the responsible use of AI in cybersecurity to prevent misuse and ensure accountability.
AI is a game changer in cybersecurity, for both good and bad. While AI gives defenders powerful tools to detect, prevent and respond to threats, it also equips attackers with superpowers to breach defenses. How we use AI for good and to mitigate the bad will determine the future of cybersecurity.
Futurism, transhumanism, bioethics, ethics, science, philosophy, artificial intelligence, personhood.
There are contexts where human cognitive and emotional intelligence takes precedence over AI, which serves a supporting role in decision-making without overriding human judgment. Here, AI “protects” human cognitive processes from things like bias, heuristic thinking, or decision-making that activates the brain’s reward system and leads to incoherent or skewed results. In the human-first mode, artificial integrity can assist judicial processes by analyzing previous law cases and outcomes, for instance, without substituting a judge’s moral and ethical reasoning. For this to work well, the AI system would also have to show how it arrives at different conclusions and recommendations, considering any cultural context or values that apply differently across different regions or legal systems.
4 – Fusion Mode:
Artificial integrity in this mode is a synergy between human intelligence and AI capabilities combining the best of both worlds. Autonomous vehicles operating in Fusion Mode would have AI managing the vehicle’s operations, such as speed, navigation, and obstacle avoidance, while human oversight, potentially through emerging technologies like Brain-Computer Interfaces (BCIs), would offer real-time input on complex ethical dilemmas. For instance, in unavoidable crash situations, a BCI could enable direct communication between the human brain and AI, allowing ethical decision-making to occur in real-time, and blending AI’s precision with human moral reasoning. These kinds of advanced integrations between humans and machines will require artificial integrity at the highest level of maturity: artificial integrity would ensure not only technical excellence but ethical robustness, to guard against any exploitation or manipulation of neural data as it prioritizes human safety and autonomy.
The question as to whether morality is innate has been hotly debated in developmental psychology for decades.
An international study with LMU participation provides evidence that our moral sense is not innate.
While LLMs are trained on massive, diverse datasets, SLMs concentrate on domain-specific data. In such cases, the data is often from within the enterprise. This makes SLMs tailored to industries or use cases, thereby ensuring both relevance and privacy.
As AI technologies expand, so do concerns about cybersecurity and ethics. The rise of unsanctioned and unmanaged AI applications within organisations, also referred to as ‘Shadow AI’, poses challenges for security leaders in safeguarding against potential vulnerabilities.
Predictions for 2025 suggest that AI will become mainstream, speeding up the adoption of cloud-based solutions across industries. This shift is expected to bring significant operational benefits, including improved risk assessment and enhanced decision-making capabilities.
One of the leading AI companies is funding academic research into algorithms that can predict humans’ moral judgements.
Scientists raise the alarm following updated research ethics guidelines on heritable human genome editing.