Редактирование: AI risk

[[File:Terminator.jpg|thumb|right|[[Terminator|The Terminator]] - a popular portrayal of an unfriendly AI]]
'''AI risk''' is the potential for artificial intelligent systems to cause unintended harm.

== Sources of harm from AI ==

AI harm might arise from:
* Bugs: the software behaves different from the specification
* Specification errors: designers didn't foresee all the circumstances properly (this includes unanticipated interactions between different modules)
* Security errors: the software gets hacked for purposes other than its original design
* AI Control Problem: an AI that can't be controlled.

The potential for harm is compounded by:
* Fierce competitive pressures, which may lead some designers to cut corners
* Much software having a "black box" nature which means that its behaviour in new circumstances is difficult to predict
* AI components being available as open source, and utilised by third parties in ways their designers didn't intend (or foresee).

== Risks from AI even in the absence of an intelligence explosion ==

Popular accounts of AI risk often focus on two factors thought to be preconditions for any major harm from AI:
* The AI become [[self-aware]]
* The AI undergoes an intelligence explosion

However, [[Viktoriya Krakovna]] points out that risks can arise without either of these factors occurring<ref>[http://futureoflife.org/2015/11/30/risks-from-general-artificial-intelligence-without-an-intelligence-explosion/ Risks From General Artificial Intelligence Without an Intelligence Explosion]</ref>. Krakovna urges AI risk analysts to pay attention to factors such as
# Human incentives: Researchers, companies and governments have professional and economic incentives to build AI that is as powerful as possible, as quickly as possible
# Convergent instrumental goals: Sufficiently advanced AI systems would by default develop drives like self-preservation, resource acquisition, and preservation of their objective functions, independent of their objective function or design.
# Unintended consequences: As in the stories of Sorcerer’s Apprentice and King Midas, you get what you asked for, but not what you wanted
# Value learning is hard: Specifying common sense and ethics in computer code is no easy feat.
# Value learning is insufficient: Even an AI system with perfect understanding of human values and goals would not necessarily adopt them
# Containment is hard: A general AI system with access to the internet would be able to hack thousands of computers and copy itself onto them, thus becoming difficult or impossible to shut down – this is a serious problem even with present-day computer viruses.

== Pathways to dangerous AIs ==

As classified by [[Roman Yampolskiy]], pathways to dangerous AIs include<ref>[http://arxiv.org/ftp/arxiv/papers/1511/1511.03246.pdf Taxonomy of Pathways to Dangerous AI]</ref>:

* On Purpose – Pre-Deployment
* On Purpose - Post Deployment 
* By Mistake - Pre-Deployment
* By Mistake - Post-Deployment
* Environment – Pre-Deployment
* Environment – Post-Deployment
* Independently - Pre-Deployment
* Independently – Post-Deployment

==AI Risk Advocates==
One of the most notable Risk Advocates in regards to AI is [[Elon Musk]], which is said to be one of the reasons behind his creation of [[OpenAI]].<ref>https://en.wikipedia.org/wiki/Open_Letter_on_Artificial_Intelligence</ref><ref>http://www.telegraph.co.uk/technology/news/11342200/Top-scientists-call-for-caution-over-artificial-intelligence.html</ref>

[[Category:Existential risks]]

== See also ==
* [[MIRI]]
== External links ==
* {{wikipedia|Existential risk from advanced artificial intelligence}}

== References ==
{{reflist}}
[[Category:Existential risks]]
[[Category:Artificial intelligence]]