Artificial Intelligence and Its Implications for Future Suffering – Foundational Research Institute. First written: 1. May 2. 01. 4; last update: 1 Dec.
Summary. Artificial intelligence (AI) will transform the world later this century. I expect this transition will be a "soft takeoff" in which many sectors of society update together in response to incremental AI developments, though the possibility of a harder takeoff in which a single AI project "goes foom" shouldn't be ruled out. If a rogue AI gained control of Earth, it would proceed to accomplish its goals by colonizing the galaxy and undertaking some very interesting achievements in science and engineering. On the other hand, it would not necessarily respect human values, including the value of preventing the suffering of less powerful creatures.
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Whether a rogue- AI scenario would entail more expected suffering than other scenarios is a question to explore further. Regardless, the field of AI ethics and policy seems to be a very important space where altruists can make a positive- sum impact along many dimensions. Expanding dialogue and challenging us- vs.- them prejudices could be valuable. Other versions of this piece*Several of the new written sections of this piece are absent from the podcast because I recorded it a while back. Introduction. This piece contains some observations on what looks to be potentially a coming machine revolution in Earth's history.
For general background reading, a good place to start is Wikipedia's article on the technological singularity. I am not an expert on all the arguments in this field, and my views remain very open to change with new information. In the face of epistemic disagreements with other very smart observers, it makes sense to grant some credence to a variety of viewpoints. Each person brings unique contributions to the discussion by virtue of his or her particular background, experience, and intuitions. To date, I have not found a detailed analysis of how those who are moved more by preventing suffering than by other values should approach singularity issues. This seems to me a serious gap, and research on this topic deserves high priority. Safeguarding Adults Board Annual Report.
In general, it's important to expand discussion of singularity issues to encompass a broader range of participants than the engineers, technophiles, and science- fiction nerds who have historically pioneered the field. I. J. Good observed in 1. The urgent drives out the important, so there is not very much written about ethical machines". Fortunately, this may be changing. Is "the singularity" crazy? In fall 2. 00. 5, a friend pointed me to Ray Kurzweil's The Age of Spiritual Machines.
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This was my first introduction to "singularity" ideas, and I found the book pretty astonishing. At the same time, much of it seemed rather implausible to me.
In line with the attitudes of my peers, I assumed that Kurzweil was crazy and that while his ideas deserved further inspection, they should not be taken at face value. In 2. 00. 6 I discovered Nick Bostrom and Eliezer Yudkowsky, and I began to follow the organization then called the Singularity Institute for Artificial Intelligence (SIAI), which is now MIRI. I took SIAI's ideas more seriously than Kurzweil's, but I remained embarrassed to mention the organization because the first word in SIAI's name sets off "insanity alarms" in listeners.
I began to study machine learning in order to get a better grasp of the AI field, and in fall 2. I switched my college major to computer science. As I read textbooks and papers about machine learning, I felt as though "narrow AI" was very different from the strong- AI fantasies that people painted. AI programs are just a bunch of hacks," I thought.
This isn't intelligence; it's just people using computers to manipulate data and perform optimization, and they dress it up as 'AI' to make it sound sexy." Machine learning in particular seemed to be just a computer scientist's version of statistics. Neural networks were just an elaborated form of logistic regression. There were stylistic differences, such as computer science's focus on cross- validation and bootstrapping instead of testing parametric models - - made possible because computers can run data- intensive operations that were inaccessible to statisticians in the 1. But overall, this work didn't seem like the kind of "real" intelligence that people talked about for general AI. This attitude began to change as I learned more cognitive science. Mitochondrial Disease In Adults Uk. Before 2. 00. 8, my ideas about human cognition were vague.
Like most science- literate people, I believed the brain was a product of physical processes, including firing patterns of neurons. But I lacked further insight into what the black box of brains might contain. This led me to be confused about what "free will" meant until mid- 2. Cognitive science showed me that the brain was in fact very much like a computer, at least in the sense of being a deterministic information- processing device with distinct algorithms and modules.