Life 3.0: being human in the age of artificial intelligence

By Anne Lauscher. 2019

622 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Safety Research, AI Ethics, Fairness & Society, Philosophy

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Cognitive Neuroscience

1. Iason Gabriel
2. Katya Klinova
3. Peter Eckersley
4. Anton Korinek

In Safety Research

1. Iason Gabriel
2. Katya Klinova
3. Pengcheng Jiao
4. Luyi Zheng
5. Ouyang Fan
6. Peter Eckersley
7. Anton Korinek

In AI Ethics, Fairness & Society

1. Iason Gabriel
2. Katya Klinova
3. Peter Eckersley
4. Dan Hendrycks
5. Anton Korinek

In Philosophy

1. Iason Gabriel
2. Katya Klinova
3. Peter Eckersley
4. Dan Hendrycks
5. Anton Korinek

Citations in the corpus

• Artificial Intelligence, Values, and Alignment (2020, background): “Such AI could be owned and operated largely by companies or foundations that use it to sup-12 port their own private goals and ends (Tegmark, 2017).”
• Artificial intelligence in online higher education: A systematic review of empirical research from 2011 to 2020 (2022, background): “Overall, a deep understanding can be achieved by conducting more empirical research to examine the roles of AI in online higher education, educational and learning theories underpinned AIEd, and the actual effects of AI on online learning quality (Gartner, 2019; Law, 2019; Tegmark, 2017).”
• Contributions and Risks of Artificial Intelligence (AI) in Building Smarter Cities: Insights from a Systematic Review of the Literature (2020, background): “Furthermore, AI is certainly seen as the most disruptive technology among them [19,20].”
• Human- versus Artificial Intelligence (2021, background): “This would imply that there is no insurmountable physical reason why machines one day cannot become much more intelligent than ourselves in all possible respects (Tegmark, 2017).”
• Impossibility and Uncertainty Theorems in AI Value Alignment (or why your AGI should not have a utility function) (2018, background): “Many of the concerns in the literature about the difficulty of aligning hypothetical future AGI systems to human values are motivated by the risk of “instrumental convergence” of those systems — the adoption of sub-goals that are disempowering of humans and other agents (Russell and Norvig 2003; Bos”
• An Overview of Catastrophic AI Risks (2023, background): “He has also expressed the sentiment that humans maintaining control over AIs is “speciesist” [15].”
• Can artificial intelligence transform higher education? (2020, neutral): “Tegmark (2017) argues that we have yet to attain the level of Artificial General Intelligence, where the processing capabilities of machines matches the cognitive capabilities of humans, while Bostrum (2017) suggests that we have endured an ‘AI Winter’ where AI proponents have suffered loss of…”
• AI and Shared Prosperity (2021, background): “Lastly, even though paid labor is currently the main source of income for the majority of humans, we do not want to rule out the possibility that far greater shared prosperity and human flourishing may be possible in the future of humanity, if all labor is replaced by sufficiently intelligent AI sys”