Archive (Page 3 of 5)

Artificial Intelligence: Challenges of Extended Intelligence

Machine learn­ing sys­tems that we have today have become so pow­er­ful and are being intro­duced into every­thing from self‐driving cars, to pre­dic­tive polic­ing, to assist­ing judges, to pro­duc­ing your news feed on Facebook on what you ought to see. And they have a lot of soci­etal impacts. But they’re very dif­fi­cult to audit.

Artificial Intelligence: Education and Personalized Learning

I think there are count­less amaz­ing oppor­tu­ni­ties for arti­fi­cial intel­li­gence and its impact on soci­ety. I think one of the areas I’m tru­ly the most excit­ed about is edu­ca­tion.

The Geographic Opportunities and Challenges of AI

I think devel­op­ments in arti­fi­cial intel­li­gence do pose a strong chal­lenge for human­i­ty. I think at a very fun­da­men­tal lev­el, peo­ple don’t quite under­stand what arti­fi­cial intel­li­gence is, yet it’s used as a buzz­word that’s going to solve every sin­gle prob­lem.

Artificial Intelligence: Society in the Loop

Some of the long‐term chal­lenges are very hypothetical—we don’t real­ly know if they will ever mate­ri­al­ize in this way. But in the short term I think AI pos­es some reg­u­la­to­ry chal­lenges for soci­ety.

Brewster Kahle’s Internet Hall of Fame 2012 Induction Speech

Back in 1980, work­ing with the arti­fi­cial intel­li­gence guys, we had this idea we were going to make smart machines. But it need­ed to read good books, don’t you think?

Forbidden Research: Why We Can’t Do That

Quite often when we’re ask­ing these dif­fi­cult ques­tions we’re ask­ing about ques­tions where we might not even know how to ask where the line is. But in oth­er cas­es, when researchers work to advance pub­lic knowl­edge, even on uncon­tro­ver­sial top­ics, we can still find our­selves for­bid­den from doing the research or dis­sem­i­nat­ing the research.

Vint Cerf Areté Medallion Q&A Elon University 2016

We’ve already been through sev­er­al sit­u­a­tions where new tech­nolo­gies come along. The Industrial Revolution removed a large num­ber of jobs that had been done by hand, replaced them with machines. But the machines had to be built, the machines had to be oper­at­ed, the machines had to be main­tained. And the same is true in this online envi­ron­ment.

Harnessing Artificial Intelligence to Target Conservation Efforts

The smart­phone is the ulti­mate exam­ple of a uni­ver­sal com­put­er. Apps trans­form the phone into dif­fer­ent devices. Unfortunately, the com­pu­ta­tion­al rev­o­lu­tion has done lit­tle for the sus­tain­abil­i­ty of our Earth. Yet, sus­tain­abil­i­ty prob­lems are unique in scale and com­plex­i­ty, often involv­ing sig­nif­i­cant com­pu­ta­tion­al chal­lenges.

What Should We Know About Algorithms?

When I go talk about this, the thing that I tell peo­ple is that I’m not wor­ried about algo­rithms tak­ing over human­i­ty, because they kind of suck at a lot of things, right. And we’re real­ly not that good at a lot of things we do. But there are things that we’re good at. And so the exam­ple that I like to give is Amazon rec­om­mender sys­tems. You all run into this on Netflix or Amazon, where they rec­om­mend stuff to you. And those algo­rithms are actu­al­ly very sim­i­lar to a lot of the sophis­ti­cat­ed arti­fi­cial intel­li­gence we see now. It’s the same under­neath.