Search Results for author:
Found 25 papers, 0 papers with code
AI Risk Skepticism, A Comprehensive Survey
In this thorough study, we took a closer look at the skepticism that has arisen with respect to potential dangers associated with artificial intelligence, denoted as AI Risk Skepticism.
Impossibility Results in AI: A Survey
Also, we added new results (theorems) such as the unfairness of explainability, the first explainability-related result in the induction category.
AI Risk Skepticism
In this work, we survey skepticism regarding AI risk and show parallels with other types of scientific skepticism.
Understanding and Avoiding AI Failures: A Practical Guide
As AI technologies increase in capability and ubiquity, AI accidents are becoming more common.
On Controllability of AI
Invention of artificial general intelligence is predicted to cause a shift in the trajectory of human civilization.
Human $\neq$ AGI
Terms Artificial General Intelligence (AGI) and Human-Level Artificial Intelligence (HLAI) have been used interchangeably to refer to the Holy Grail of Artificial Intelligence (AI) research, creation of a machine capable of achieving goals in a wide range of environments.
Unpredictability of AI
The young field of AI Safety is still in the process of identifying its challenges and limitations.
Personal Universes: A Solution to the Multi-Agent Value Alignment Problem
AI Safety researchers attempting to align values of highly capable intelligent systems with those of humanity face a number of challenges including personal value extraction, multi-agent value merger and finally in-silico encoding.
Emergence of Addictive Behaviors in Reinforcement Learning Agents
This paper presents a novel approach to the technical analysis of wireheading in intelligent agents.
Why We Do Not Evolve Software? Analysis of Evolutionary Algorithms
In this paper, we review the state-of-the-art results in evolutionary computation and observe that we do not evolve non trivial software from scratch and with no human intervention.
Human Indignity: From Legal AI Personhood to Selfish Memes
It is possible to rely on current corporate law to grant legal personhood to Artificially Intelligent (AI) agents.
Optical Illusions Images Dataset
Human vision is capable of performing many tasks not optimized for in its long evolution.
Building Safer AGI by introducing Artificial Stupidity
Artificial Intelligence (AI) achieved super-human performance in a broad variety of domains.
A Psychopathological Approach to Safety Engineering in AI and AGI
The complexity of dynamics in AI techniques is already approaching that of complex adaptive systems, thus curtailing the feasibility of formal controllability and reachability analysis in the context of AI safety.
Detecting Qualia in Natural and Artificial Agents
The Hard Problem of consciousness has been dismissed as an illusion.
Guidelines for Artificial Intelligence Containment
With almost daily improvements in capabilities of artificial intelligence it is more important than ever to develop safety software for use by the AI research community.
Evaluating race and sex diversity in the world's largest companies using deep neural networks
Diversity is one of the fundamental properties for the survival of species, populations, and organizations.
The Singularity May Be Near
Toby Walsh in 'The Singularity May Never Be Near' gives six arguments to support his point of view that technological singularity may happen but that it is unlikely.
Artificial Intelligence Safety and Cybersecurity: a Timeline of AI Failures
We suggest that both the frequency and the seriousness of future AI failures will steadily increase.
Verifier Theory and Unverifiability
Despite significant developments in Proof Theory, surprisingly little attention has been devoted to the concept of proof verifier.
Unethical Research: How to Create a Malevolent Artificial Intelligence
Cybersecurity research involves publishing papers about malicious exploits as much as publishing information on how to design tools to protect cyber-infrastructure.
Taxonomy of Pathways to Dangerous AI
In order to properly handle a dangerous Artificially Intelligent (AI) system it is important to understand how the system came to be in such a state.
From Seed AI to Technological Singularity via Recursively Self-Improving Software
Software capable of improving itself has been a dream of computer scientists since the inception of the field.
The Universe of Minds
The paper attempts to describe the space of possible mind designs by first equating all minds to software.
