000 02234 a2200229 4500
008 230106b |||||||| |||| 00| 0 eng d
020 _a9780674278660
082 _a006.3
_bLAR
100 _aLarson, Erik J.
245 _aMyth of artificial intelligence: why computers can’t think the way we do
260 _bBelknap Press of Harvard University Press,
_c2021.
_aCambridge:
300 _aviii, 312p.;
_bpbk;
_c23cm.
504 _aIncludes notes and index
520 _aFuturists insist that AI will soon eclipse the capacities of the most gifted human mind. What hope do we have against superintelligent machines? But we aren’t really on the path to developing intelligent machines. In fact, we don’t even know where that path might be. A tech entrepreneur and pioneering research scientist working at the forefront of natural language processing, Erik Larson takes us on a tour of the landscape of AI to show how far we are from superintelligence, and what it would take to get there. Ever since Alan Turing, AI enthusiasts have equated artificial intelligence with human intelligence. This is a profound mistake. AI works on inductive reasoning, crunching data sets to predict outcomes. But humans don’t correlate data sets: we make conjectures informed by context and experience. Human intelligence is a web of best guesses, given what we know about the world. We haven’t a clue how to program this kind of intuitive reasoning, known as abduction. Yet it is the heart of common sense. That’s why Alexa can’t understand what you are asking, and why AI can only take us so far. Larson argues that AI hype is both bad science and bad for science. A culture of invention thrives on exploring unknowns, not overselling existing methods. Inductive AI will continue to improve at narrow tasks, but if we want to make real progress, we will need to start by more fully appreciating the only true intelligence we know—our own. https://www.hup.harvard.edu/catalog.php?isbn=9780674983519
650 _aNatural language processing--Computer science
650 _aArtificial intelligence
650 _aLogic
650 _aNeurosciences
650 _aInference
650 _aIntellect
942 _2ddc
_cTD
999 _c55161
_d55161