Tag: Stanford University

TEDMED has forgotten Elizabeth Holmes

Sunday, 7 April, 2019

They say the internet never forgets and the maxim has proved costly to lots of people who thought those old tweets or videos had been cobwebbed forever. TEDMED seems to be an exception to the rule, though. It has forgotten Elizabeth Holmes. Let’s back up here for a moment. TEDMED is “the independent health and medicine edition of the world-famous TED conference, dedicated to “ideas worth spreading.”

And Elizabeth Holmes? She’s the Silicon Valley scam artist who founded a company, Theranos, at the age of 19, dropping out of Stanford University and raising hundreds of millions of VC dollars to create a device she claimed would change health care with a fingerprick of blood. From bedrooms to battlefields to laboratories, it would make medical information more affordable. In her brief career, Holmes became a feminist icon, rejoicing in her own triumph over the bro-dominated world of tech. She once ended a Theranos film by declaring, “I always say that next to every glass ceiling there’s an iron lady.” Inevitably, the media elevated her a superwoman fighting for human rights, and the huge wealth she temporarily generated was celebrated as a deserved byproduct of her brilliant mind.

Search the TEDMED site today and you’ll find no mention of Elizabeth Holmes, though. She’s been erased from its history. Still, YouTube has a clip of the talk she delivered at TEDMED in 2014. “I believe. The individual. Is the answer. To the challenges of healthcare.” No wonder TEDMED deleted it.


Insh-AI: WOTF on Ash Wednesday

Wednesday, 14 February, 2018 0 Comments

Back in November last year, Wired ran an article titled Inside The First Church of Artificial Intelligence. The writer, Mark Harris, introduced readers to Anthony Levandowski, the “unlikely prophet” of a new religion of artificial intelligence called Way of the Future (WOTF). Levandowski’s church, we learn, will focus on “the realization, acceptance, and worship of a Godhead based on Artificial Intelligence (AI) developed through computer hardware and software.”

Last Sunday in the Sunday Times, Niall Ferguson, Senior Fellow at the Hoover Institution at Stanford University, asked “Shall we begin to worship the machines — to propitiate them with prayers, or even sacrifices?” And, provocatively proposed: “Perhaps we shall need to devise an AI equivalent of “Inshallah” — Insh-AI, perhaps.” Ferguson’s syndicated column has the oddly banal title, The machines ate my homework, but it offers food for serious thought, especially today, Ash Wednesday. Ashes to ashes AI, he says, is all about “getting computers to think like a species that had evolved brains much bigger than humans — in other words, not like humans at all.” One consequence of this might be to “return humanity to the old world of mystery and magic. As machine learning steadily replaces human judgment, we shall find ourselves as baffled by events as our pre-modern forefathers were.”

What will become of us then? Will we, in despair, in hope, follow WOFT? Ferguson quotes the German sociologist Max Weber who argued that modernity replaced mystery with rationalism and as a result people “said goodbye to magic and entered an ‘iron cage’ of rationality and bureaucracy.” If AI leads to a re-mystification of the world and a revival of magical thinking, Ferguson knows what he’s going to do: “I’m staying put in Weber’s iron cage,” he says.

But you can’t put ashes on an AI and not everyone aspires to being caged.


AI and terrific slang

Friday, 9 June, 2017 0 Comments

A lot of work on natural language processing involves designing algorithms that can understand meaning in written and spoken language and respond intelligently. Christopher Manning, Professor of Computer Science and Linguistics at Stanford University, relies on an offshoot of artificial intelligence known as “deep learning” to design algorithms that can teach themselves to understand meaning and adapt to new or evolving uses of language, such as slang. Andrew Myers spoke with Manning for Futurity about how AI (artificial intelligence) can teach itself slang. Snippet:

Can natural language processing adapt to new uses of language, to new words or to slang?

“That was one of the big limitations of early approaches. Words tend to pick up different usages and even meanings over time, often very remarkably. The world ‘terrific’ used to have a highly negative meaning — something that terrifies. Only recently has it become a positive term.

That’s one of the areas I’ve been involved in. Natural language processing, even if trained in the earlier meaning, can look at a word like ‘terrific’ and see the positive context. It picks up on those soft changes in meaning over time. It learns by examining language as it is used in the world.”