Teams designing AI should include linguistics and philosophy experts, parents, young people, everyday people with different life experiences from different socio-economic backgrounds.

• 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.

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Welcome to Impact Theory, I’m Tom Bilyeu and in today’s episode, Nick Bostrom and I dive into the moral and societal implications of AI as it becomes increasingly advanced.

Nick Bostrom is a leading philosopher, author, and expert on AI here to discuss the future of AI, its challenges, and its profound impact on society, meaning, and our pursuit of happiness.

We touch on treating AI with moral consideration, the potential centralization of power, automation of critical sectors like police and military, and the creation of hyper-stimuli that could impact society profoundly.

We also discuss Nick’s book, Deep Utopia, and what the ideal human life will look like in a future dominated by advanced technology, AI, and biotechnology.

Our conversation navigates through pressing questions about AI aligning with human values, the catastrophic consequences of powerful AI systems, and the need for deeper philosophical and ethical considerations as AI continues to evolve.

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.

“An Unscientific American” discusses the resignation of Laura Helmuth from her position as editor-in-chief at Scientific American. The author, Michael Shermer, argues that her departure exemplifies the risks of blending facts with ideology in scientific communication.

Helmuth faced backlash after posting controversial remarks on social media regarding political views, which led to public criticism and her eventual resignation. Shermer reflects on how the magazine’s editorial direction has shifted towards progressive ideology, suggesting this has compromised its scientific integrity. He notes that had Helmuth made disparaging comments about liberal viewpoints, her outcome would likely have been more severe.

The article critiques Scientific American for endorsing positions on gender and race that Shermer sees as ideologically driven rather than based on scientific evidence. He expresses concern that such ideological capture within scientific publications can distort facts and undermine credibility.

For more details, you can read the full article here.

About the Author.
Michael Shermer is a prominent science writer and the founder of the Skeptics Society. He is known for his work promoting scientific skepticism and questioning pseudoscience. Shermer is also the author of several books on belief, morality, and the nature of science, including The Believing Brain and The Moral Arc.
https://quillette.com/2024/11/21/an-unscientific-american-sc…signation/
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Quillette is an Australian-based online magazine that focuses on long-form analysis and cultural commentary. It is politically non-partisan, but relies on reason, science, and humanism as its guiding values.

Quillette was founded in 2015 by Australian writer Claire Lehmann. It is a platform for free thought and a space for open discussion and debate on a wide range of topics, including politics, culture, science, and technology.

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.