Gilbert Harman’s famous principle of Clutter Avoidance commands that “one should not clutter one’s mind with trivialities". Many epistemologists have been inclined to accept Harman’s principle, or something like it. This is significant because the principle appears to have robust implications for our overall picture of epistemic normativity. Jane Friedman (2018) has recently argued that one potential implication is that there are no genuine purely evidential norms on belief revision. In this paper, we present some new objections to a suitably (...) formulated version of the clutter principle qua norm on belief revision. Moreover, we argue that the clutter principle is best understood as a norm on non-doxastic stages of inquiry. In our view, it is a norm of asking and considering questions rather than a norm of settling on an answer to a question by forming a belief. (shrink)

Doxastic wronging is wronging that occurs in virtue of a belief. What epistemic significance, if any, does doxastic wronging have for the normativity of inquiry? Recently, some philosophers have defended views according to which doxastic wronging has an epistemic impact on the norms governing belief formation and revision. In this paper, I sketch a theory of the zetetic significance of doxastic wronging that denies its epistemic significance. In other words, although doxastic wronging is relevant to the normativity of inquiry, it (...) is irrelevant to the normativity of belief formation and revision. To defend this thesis, I sketch a framework for thinking about zetetic structure and I combine this framework with an independently attractive picture of epistemic normativity according to which answers to questions are to be settled in whatever way is best supported by the evidence. (shrink)

Better instruments to predict the future evolution of artificial intelligence (AI) are needed, as the destiny of our civilization depends on it. One of the ways to such prediction is the analysis of the convergent drives of any future AI, started by Omohundro. We show that one of the convergent drives of AI is a militarization drive, arising from AI’s need to wage a war against its potential rivals by either physical or software means, or to increase its bargaining power. (...) This militarization trend increases global catastrophic risk or even existential risk during AI takeoff, which includes the use of nuclear weapons against rival AIs, blackmail by the threat of creating a global catastrophe, and the consequences of a war between two AIs. As a result, even benevolent AI may evolve into potentially dangerous military AI. The type and intensity of militarization drive depend on the relative speed of the AI takeoff and the number of potential rivals. We show that AI militarization drive and evolution of national defense will merge, as a superintelligence created in the defense environment will have quicker takeoff speeds, but a distorted value system. We conclude with peaceful alternatives. (shrink)

Existential risks threaten the future of humanity, but they are difficult to measure. However, to communicate, prioritize and mitigate such risks it is important to estimate their relative significance. Risk probabilities are typically used, but for existential risks they are problematic due to ambiguity, and because quantitative probabilities do not represent some aspects of these risks. Thus, a standardized and easily comprehensible instrument is called for, to communicate dangers from various global catastrophic and existential risks. In this article, inspired by (...) the Torino scale of asteroid danger, we suggest a color coded scale to communicate the magnitude of global catastrophic and existential risks. The scale is based on the probability intervals of risks in the next century if they are available. The risks’ estimations could be adjusted based on their severities and other factors. The scale covers not only existential risks, but smaller size global catastrophic risks. It consists of six color levels, which correspond to previously suggested levels of prevention activity. We estimate artificial intelligence risks as “red”, while “orange” risks include nanotechnology, synthetic biology, full scale nuclear war and a large global agricultural shortfall (caused by regional nuclear war, coincident extreme weather, etc.) The risks of natural pandemic, supervolcanic eruption and global warming are marked as “yellow” and the danger from asteroids is “green”. -/- Keywords: global catastrophic risks; existential risks; Torino scale; policy; risk probability . (shrink)

Artificial Intelligence is part of the Industrial Revolution 4.0 and already exists today. This shows that the future has come and everyone must prepare for the implementation of Artificial Intelligence to face the transformation of the digital era, especially the world of education. The community service workshop was attended by 66 participants, namely students, teachers, and structural officials of SMK Negeri 2 Singkawang. The workshop was held using demonstration methods, lectures, discussions and question and answer. This workshop provides information to (...) teachers and students about the importance of Artificial Intelligence (AI) in the digital transformation process. For teachers and students at SMKN 2 Singkawang it was introduced that algorithms or artificial intelligence methods could be given simply by representing problems into simple solutions with several examples of implementing artificial intelligence using Microsoft Excel and utilizing VBA macros. (shrink)

In this paper, we focus on the most efficacious AI applications for life extension and anti-aging at three expected stages of AI development: narrow AI, AGI and superintelligence. First, we overview the existing research and commercial work performed by a select number of startups and academic projects. We find that at the current stage of “narrow” AI, the most promising areas for life extension are geroprotector-combination discovery, detection of aging biomarkers, and personalized anti-aging therapy. These advances could help currently living (...) people reach longevity escape velocity and survive until more advanced AI appears. When AI comes close to human level, the main contribution to life extension will come from AI integration with humans through brain-computer interfaces, integrated AI assistants capable of autonomously diagnosing and treating health issues, and cyber systems embedded into human bodies. Lastly, we speculate about the more remote future, when AI reaches the level of superintelligence and such life-extension methods as uploading human minds and creating nanotechnological bodies may become possible, thus lowering the probability of human death close to zero. We suggest that medical AI based superintelligence could be safer than, say, military AI, as it may help humans to evolve into part of the future superintelligence via brain augmentation, uploading, and a network of self-improving humans. Medical AI’s value system is focused on human benefit. (shrink)