<story><title>‘The discourse is unhinged’: how the media gets AI wrong</title><url>https://www.theguardian.com/technology/2018/jul/25/ai-artificial-intelligence-social-media-bots-wrong</url></story><parent_chain></parent_chain><comment><author>dalbasal</author><text>This sort of sensationalism, in general, is so completely ingrained into reporting that it&amp;#x27;s hard to separate from journalism itself. It&amp;#x27;s part of the journalistic style, an inevitability of the medium.&lt;p&gt;We see an article, click a link, by a paper, but we are never committing to more than a second or two of attention at a time. The headline makes you read the byline. The byline gets you reading the second sentence. At every step, a journalist loses most of her readers. The winning strategy is to increase &amp;quot;story,&amp;quot; play to existing opinions, be sensational, use bait...  There are flavours and degrees, but by and large writing like this is n inevitability of the medium, of journalism.&lt;p&gt;If you are reporting on programs that &amp;quot;developed a type of machine-English patois to communicate between themselves..&amp;quot; you are reporting on whether or not the skynet singularity is coming, almost certainly.&lt;p&gt;If we want something different, I think we&amp;#x27;ll need a medium change.&lt;p&gt;Personally, I was hoping e-readers would catalyze a new medium subtype: 30-100 page mini books. A lot of &amp;quot;news cycle..&amp;quot; the drip, drip, sensation of the day journalism just isn&amp;#x27;t a good way of understanding anything.&lt;p&gt;What happened between North Korea and the US this year? What&amp;#x27;s been happening with the Syrian war? Brexit as of July 2018...?  I would be very happy to exchange the daily&amp;#x2F;weekly news bulletins for monthly&amp;#x2F;quarterly mini books.</text></comment>
<story><title>‘The discourse is unhinged’: how the media gets AI wrong</title><url>https://www.theguardian.com/technology/2018/jul/25/ai-artificial-intelligence-social-media-bots-wrong</url></story><parent_chain></parent_chain><comment><author>jokoon</author><text>Success in developing working AI is not so much of a big step in progress for AI in general.&lt;p&gt;It would be more interesting if we could understand what happens in those black boxes, and synthesize it. All we see is showcase projects and services, but never something you can run on a client computer.&lt;p&gt;It really looks like machine learning is just brute forcing problems until you have a partial solution key to a problem, without understanding how it works internally. Granted, it&amp;#x27;s progress, but why isn&amp;#x27;t it possible to use the data of a trained ML network for further analysis? I see many models of learning, but not a lot of analysis or simplification of the resulting data.&lt;p&gt;I would have thought AI would help science understand what intelligence is, but obviously it&amp;#x27;s always money first, science later. You often see a lot of tools and models, but not a lot of good insights.</text></comment>