Zuckerberg Mentor-Turned-Critic Calls Out Silicon Valley in "Zucked"

March 13, 2019

Roger McNamee, Facebook investor and former mentor to CEO Mark Zuckerberg, is calling for change when it comes to social media and tech in his new book "Zucked: Waking Up to the Facebook Catastrophe." McNamee discusses the issues driving his latest work and what he thinks should be done next.

FULL TRANSCRIPT

Speaker 1: So you are critical of Facebook, uh,

Speaker 1: but not of the people itself

Speaker 1: because you actually write here that,

Speaker 1: uh, I don't think

Speaker 1: this is about the people when somebody asked,

Speaker 1: uh, if you, uh,

Speaker 1: Zuckerberg should step down,

Speaker 1: you said I believe this is about the business model,

Speaker 1: if you don't change the business model,

Speaker 1: it doesn't matter who's running it.

Speaker 2: That's, I believe that to the bottom of my heart.

Speaker 2: I, I had a wonderful relationship with Mark as

Speaker 2: a mentor back 2006 to 2009.

Speaker 2: You know I had

Speaker 2: a wonderful relationship with Sheryl Sandberg,

Speaker 2: helped bring her into the company,

Speaker 2: and I have enormous respect for them

Speaker 2: just as I do for Larry and Sergey at Google,

Speaker 2: you know I think these are brilliant people,

Speaker 2: but I think the culture of Silicon Valley,

Speaker 2: the culture of the business world today in

Speaker 2: this unregulated environment and

Speaker 2: combined with the sort of brilliance

Speaker 2: of these, these people,

Speaker 2: and the sort of general sense of

Speaker 2: exceptionalism this notion that

Speaker 2: there are no rules that apply

Speaker 2: to the smartest people in the Valley,

Speaker 2: that's what got us into trouble and,

Speaker 2: you know, when I look at this,

Speaker 2: it's now become a huge issue for democracy,

Speaker 2: for public health, for privacy

Speaker 2: and frankly for innovation and growth.

Speaker 1: So when do you think Facebook

Speaker 1: crossed the line in its business model?

Speaker 2: You know I wish I knew Hope.

Speaker 2: I mean the truth of the matter is I'm a lifetime male,

Speaker 2: I se- I spent 35 years covering

Speaker 2: tech and I was at the tail end of my career.

Speaker 2: You know, Facebook was one of the last big

Speaker 2: investments I made and I

Speaker 2: wasn't paying close enough attention

Speaker 2: so I missed th- the inflection.

Speaker 2: When I stopped being an insider in 2009, so a decade ago,

Speaker 2: they didn't yet have the current business model

Speaker 2: that really sort

Speaker 2: of came in 2012,2013.

Speaker 2: And the truth is it was invented by Google in 2002,

Speaker 2: it was really this notion that when Google is

Speaker 2: improving the search results in 2002,

Speaker 2: they noticed that they

Speaker 2: only need about one percent of the day,

Speaker 2: they gather to do that.

Speaker 2: And so they went to see was there any value in

Speaker 2: the rest of the data and they just got wow,

Speaker 2: there's some behavioral prediction.

Speaker 2: So then they decide, well,

Speaker 2: we need to know who these people are.

Speaker 2: So they create Gmail

Speaker 2: and then they basically tell you we're,

Speaker 2: we're going to look at your messages

Speaker 2: because we're trying to find out what you think.

Speaker 2: And so at Gmail,

Speaker 2: they not only lo- find out who people are,

Speaker 2: they find out if you're trying to behavioral prediction.

Speaker 2: E-mails are a really great way to

Speaker 2: find out where people are going to do next.

Speaker 2: Then they do Google Maps so we're going to

Speaker 2: find out where everybody is and

Speaker 2: they add all of these things and then

Speaker 2: they start doing street view where they drive

Speaker 2: in public places and basically create

Speaker 2: a market for the data

Speaker 2: that used to be shared by all of us.

Speaker 1: Right.

Speaker 2: And then they do Google Glass to

Speaker 2: kind of get in our face and do that up close.

Speaker 2: And the problem with this model is that,

Speaker 2: they've basically taken all of

Speaker 2: this stuff without our permission.

Speaker 2: You know, yeah, we may check off a box in the thing,

Speaker 2: but we don't actually know what we're doing, right?

Speaker 2: And that they've gone to great pains to hide it.

Speaker 2: And Google perfected this model,

Speaker 2: they've been doing for a long time to the point where

Speaker 2: first they get a behavior prediction, then they create.

Speaker 1: Right. But your book is about Facebook.

Speaker 2: No, it's about the whole problem. It starts with

Speaker 2: Facebook [OVERLAPPING] because I was Mark's mentor.

Speaker 2: And so that's what I saw

Speaker 2: first and plus it's a great title, right.

Speaker 1: Yes, of course.

Speaker 2: And so that's why I went,

Speaker 2: but it's really about this whole model.

Speaker 2: So it's Google, Facebook, Amazon, Microsoft, Horizon.

Speaker 3: As Mark's mentor, what's

Speaker 3: fundamentally different about the Mark that

Speaker 3: you knew and the Mark that is

Speaker 3: post Instagram acquisition,

Speaker 3: [OVERLAPPING] WhatsApp acquisition.

Speaker 2: Brad I wish I knew.

Speaker 2: I loved Mark, I thought he

Speaker 2: was a really great person to work with.

Speaker 2: And again, he had lots of

Speaker 2: mentors when I was there and eventually

Speaker 2: the business became more mature and

Speaker 2: so I was not the right guy to keep doing that.

SPEAKER 1: I think success gave everybody in

SPEAKER 1: that company a sense

SPEAKER 1: that everything they touch turn to gold.

SPEAKER 1: They became resistant to any kind of criticism or

SPEAKER 1: negative feedback and I think it got very

SPEAKER 1: hard for them to imagine that

SPEAKER 1: anybody would use their products differently than

SPEAKER 1: they intended and so as a consequence when

SPEAKER 1: I went to them in October of 2016.

SPEAKER 1: I wasn't expecting him to kind of immediately roll over,

SPEAKER 1: but I was hoping they would do

SPEAKER 1: an investigation and figure out,

SPEAKER 1: was there a structural problem with the ad products?

SPEAKER 1: With the algorithms and

SPEAKER 1: the business model that let bad people

SPEAKER 1: hurt innocent people and then of course at

SPEAKER 1: the election let people change the outcome of elections.

FEMALE 1: Have you heard from Zuckerberg after?

SPEAKER 1: I haven't heard from anybody at Facebook since

SPEAKER 1: February 2017 and I understand that also.

SPEAKER 1: I was the wrong messenger for market share.

SPEAKER 1: I mean I spent three months privately trying to

SPEAKER 1: persuade Facebook to do what

SPEAKER 1: Johnson and Johnson did with

SPEAKER 1: Tylenol in 1983 when somebody poisoned bottles,

SPEAKER 1: and what Boeing should have done with the 737 MAX,

SPEAKER 1: which is to recognize your first duty is to

SPEAKER 1: protect the people who use your product and you have

SPEAKER 1: to just stop doing business long

SPEAKER 1: enough to find the problems and fix them

SPEAKER 1: and you know for

SPEAKER 1: whatever reason they didn't find that helpful and so,

SPEAKER 1: that's when I became an activist.

SPEAKER 2: For Facebook, what should consent

SPEAKER 2: requirements entail for leveraging people's data?

SPEAKER 1: I think the great question to ask Brad is,

SPEAKER 1: why is it legal for companies to

SPEAKER 1: make a third party market in private data.

SPEAKER 1: Why is it legal for

SPEAKER 1: credit card processors to

SPEAKER 1: sell our credit card transaction history.

SPEAKER 1: Why is it legal for

SPEAKER 1: cell phone companies to sell our location.

SPEAKER 1: Why is it legal for

SPEAKER 1: health apps to sell our wellness data.

SPEAKER 1: Why is it legal for anybody to

SPEAKER 1: sell data about where we go on the Internet.

SPEAKER 1: Why is it legal to even collect data on minors.

SPEAKER 1: I think that we have to roll all of that stuff

SPEAKER 1: back and then ask the question, when is it okay?

SPEAKER 2: Well, their argument is that, they're

SPEAKER 2: just indexing it and

SPEAKER 2: then leveraging it to put ads on top.

SPEAKER 1: No! That is their-that is

SPEAKER 1: their argument but that's

SPEAKER 1: not what they're actually doing.

SPEAKER 1: What they're really doing is they're making

SPEAKER 1: behavior of predictions and then using

SPEAKER 1: filter bubbles and they're using

SPEAKER 1: recommendation engines to make those things come

SPEAKER 1: true and let me give you an example of

SPEAKER 1: the kind of thing we should be worried about.

SPEAKER 1: So, when you go into

SPEAKER 1: it like a news site and they ask you,

SPEAKER 1: are you a robot?

SPEAKER 1: Look at these pictures, right?

SPEAKER 1: Do you see the cars or do you see the street signs.

SPEAKER 1: That's called captcha, It's a Google product.

SPEAKER 1: Well captcha isn't really

SPEAKER 1: to figure out if you're a human.

SPEAKER 1: It's to help train

SPEAKER 1: their artificial intelligence for the car.

SPEAKER 1: They figure out you're a human from

SPEAKER 1: the mouth's movement but here's the deal,

SPEAKER 1: if I get a little bit older and

SPEAKER 1: my mouth's movement gets slower

SPEAKER 1: and let's say it gets shaky.

SPEAKER 1: That might be the first sign of

SPEAKER 1: something like Parkinson's disease.

SPEAKER 1: Now, they're under no legal requirement

SPEAKER 1: to alert me that I may have a neurological problem.

SPEAKER 1: In fact, they're not even governed by HIPAA.

SPEAKER 1: So, they don't even have to protect my privacy.

SPEAKER 1: They're free to sell that to

SPEAKER 1: the highest bidder in

SPEAKER 1: the United States that's almost certainly

SPEAKER 1: my insurance company who wants to raise

SPEAKER 1: my rates or terminate my insurance and my point here is,

SPEAKER 1: markets are about both sides

SPEAKER 1: having roughly equal information.

SPEAKER 1: Now, we have this situation where

SPEAKER 1: any company goes to market has to go through Google,

SPEAKER 1: Facebook or Amazon who

SPEAKER 1: have perfect information on everybody and

SPEAKER 1: all we have is what they choose to show

SPEAKER 1: us and I just want to have that conversation.

SPEAKER 1: To me that-that's what the book is about.

SPEAKER 1: That's what this whole debate-with

SPEAKER 1: 2020 with the election coming up.

SPEAKER 1: We have the perfect time.

SPEAKER 1: Every candidate should have to

SPEAKER 1: declare what they're going to do about this stuff.

FEMALE 1: For sure. So, you have

FEMALE 1: a new Congress now and you've got people in there

FEMALE 1: who are looking at this and you're also very tech savvy

FEMALE 1: and we understand it, which is fantastic.

FEMALE 1: We know regulation is always

FEMALE 1: slow to catch up to innovation, right?

SPEAKER 1: Yeah that's true.

FEMALE 1: So-So we maybe are just as a-

FEMALE 1: as a budding industry Digital media is right?

FEMALE 1: Maybe that is a -really quick.

FEMALE 1: I do agree with you in a lot of ways that

FEMALE 1: social media you say has enabled

FEMALE 1: personal views that have previously

FEMALE 1: kept in check by social pressure as well.

FEMALE 1: But is it too late to roll these things back in

FEMALE 1: a social culture that we've

FEMALE 1: developed through these platforms.

SPEAKER 1: This is the really good news.

SPEAKER 1: So, the first thing is we're

SPEAKER 1: not going to lose the things we

SPEAKER 1: like in this transition, because one,

SPEAKER 1: these guys would- they're not going to be

SPEAKER 1: unprofitable if we make the changes I'm

SPEAKER 1: talking about they would be insane to

SPEAKER 1: leave the market and how long

SPEAKER 1: do you think it would take people to

SPEAKER 1: have alternatives to these products.

SPEAKER 1: You could create alternate-I

SPEAKER 1: was at a tech thing the other day I said,

SPEAKER 1: what do you think the over and

SPEAKER 1: under is and how long it would

SPEAKER 1: take you to replace Facebook and people said two weeks.

FEMALE 1: I mean the platforms and satellites and

FEMALE 1: even the behaviors that

FEMALE 1: we've adopted as a result of this, okay?

SPEAKER 1: But I'm saying a lot of those behaviors are not

SPEAKER 1: actually helping us the way we think and here's my point.

SPEAKER 1: I don't think these companies are innovative at all.

SPEAKER 1: I think they've actually frozen

SPEAKER 1: innovation in terms of what they give us.

SPEAKER 1: Their innovations are entirely

SPEAKER 1: about how they suck profits

SPEAKER 1: out of customers and I think that part's unhealthy.

SPEAKER 1: So my point to you here is.

SPEAKER 1: I've spent time with

SPEAKER 1: the antitrust division of the Justice Department.

SPEAKER 1: I've spent time with the FTC and they

SPEAKER 1: are really digging into these issues because they

SPEAKER 1: matter and the thing people know is that any trust is

SPEAKER 1: a pro-growth form of

SPEAKER 1: intervention in tech the history is amazing.

SPEAKER 1: Every inter trust and

SPEAKER 1: every antitrust intervention has created

SPEAKER 1: a new industry and

SPEAKER 1: massive innovation and I

SPEAKER 1: believe the same thing would be

SPEAKER 1: true here and you're right Hope.

SPEAKER 1: It's going to take a little time to get all this done,

SPEAKER 1: but the important thing is for

SPEAKER 1: people to get engaged in the conversation.

SPEAKER 1: To understand what's at stake here,

SPEAKER 1: because-again I've got nothing against these people.

SPEAKER 1: I think they're really smart but I think they've

SPEAKER 1: acquired a political power without getting

SPEAKER 1: elected and without any accountability and

SPEAKER 1: that political power right now is

SPEAKER 1: destabilizing too many things

SPEAKER 1: in our economy and our society.

SPEAKER 2: Well, coming back to his point a little bit

SPEAKER 2: here and you've said this in the past,

SPEAKER 2: that Facebook is terrible for America.

SPEAKER 2: It's driving a lot of how we think

SPEAKER 2: about each activity that we do on a day in day out basis.

SPEAKER 2: In your eyes there and you mentioned

SPEAKER 2: the 2020 election I want to

SPEAKER 2: come back to that in your eyes,

SPEAKER 2: what should the platform be doing to

SPEAKER 2: prepare for 2020 election knowing that

SPEAKER 2: it's inevitable that there will be some sort

SPEAKER 2: of influence that their platform at least have.

SPEAKER 1: I think the most impactful thing they could do

SPEAKER 1: would be to voluntarily withdraw

SPEAKER 1: from having any targeted election advertising in

SPEAKER 1: the last two-three weeks before

SPEAKER 1: the camp- before the election itself.

SPEAKER 1: To do that would be an amazing thing.

SPEAKER 1: I mean right now Mark offered that they're going to

SPEAKER 1: withdraw from any country that

SPEAKER 1: has either a human rights violation policy or privacy

SPEAKER 1: felt-just withdrawing for a few weeks

SPEAKER 1: at the end of the campaign,

SPEAKER 1: because that voter suppression which

SPEAKER 1: is so easy to do on these platforms,

SPEAKER 1: because the country is polarized and the

SPEAKER 1: products -you don't have to

SPEAKER 1: convince people of anything on these things.

SPEAKER 1: You just need to scare them

SPEAKER 1: and then blame the other guy or blame

SPEAKER 1: both guys and so that would be the thing I think

SPEAKER 1: is most important because it really bothers me.

SPEAKER 1: Facebook created that database of political ads

SPEAKER 1: and then they blocked

SPEAKER 1: ProPublica from doing any research on it,

SPEAKER 1: which is just like guys come on!

SPEAKER 1: ProPublica as the good guys, right?

SPEAKER 1: You got to let them do that.

FEMALE 1: Roger, do we look at Apple,

FEMALE 1: Microsoft differently because they would argue

FEMALE 1: that they are not making money off of our data.

SPEAKER 1: So, Microsoft is definitely making money off our data.

SPEAKER 1: So, Microsoft remember they've got LinkedIn.

SPEAKER 1: They've got BING the search engine

SPEAKER 1: and they are huge in A.I, okay?

SPEAKER 1: So, I would say Microsoft was late

SPEAKER 1: to the party but they want to be right there.

SPEAKER 1: I think Apple is different.

SPEAKER 1: Apple is taking a different thing.

SPEAKER 1: Sales force is taking a different thing

SPEAKER 1: and IBM at least in its A.I.

SPEAKER 1: business is attempting to be

SPEAKER 1: ethical and again we'll have to see the results

SPEAKER 1: but what I'm looking

SPEAKER 1: at right now is I think the guys you've

SPEAKER 1: got to watch out for are Google by a mile.

SPEAKER 1: Then Facebook and Amazon,

SPEAKER 1: Verizon and Microsoft those are the five people who

SPEAKER 1: have- if you will

SPEAKER 1: this data economy working for them in one way or another.

FEMALE 1: And just lastly, this pivot to privacy,

FEMALE 1: Mark Zuckerberg's latest post.

FEMALE 1: All right we're going to femoral encryption.

SPEAKER 1: That's a dodge. It's all about avoiding responsibility

SPEAKER 1: for the hate speech and

SPEAKER 1: all the divisive stuff that's on there.

SPEAKER 1: If it's encrypted end-to-end,

SPEAKER 1: then they can go, Hey! I can't see it.

SPEAKER 1: The truth of this is,

SPEAKER 1: I love what he said about getting out

SPEAKER 1: of the countries which have the bad policies

SPEAKER 1: on human rights and-but

SPEAKER 1: the other part of what's wrong with

SPEAKER 1: that whole conversation is that

SPEAKER 1: 99 percent of the value is not the stuff you put in.

SPEAKER 1: Right? What you put in is one percent.

SPEAKER 1: The 99 is the metadata.

SPEAKER 1: It's all the data they acquire in other places.

SPEAKER 1: All the things they get from surveillance

SPEAKER 1: and he's told you,

SPEAKER 1: flat out in his Jonathan Zittrain interview that he's

SPEAKER 1: not going to end those practices

SPEAKER 1: and -i- until we force them to. They're not going to.

FEMALE 1: How do we fix this business model because we got to go?

SPEAKER 1: Yeah we got-we got to eliminate

SPEAKER 1: the collection and the trading of that data.

SPEAKER 1: No more credit card data.

SPEAKER 1: No more personal health data.

SPEAKER 1: No more location data.

SPEAKER 1: No more Internet travel data- and they're all

SPEAKER 1: going to squawk like hell and I go- I get it guys.

SPEAKER 1: We're going to get rid of it, then we're going to have

SPEAKER 1: the conversation about what's legit.