Thursday, January 31, 2019

Zucked -- Roger McNamee's Wake Up Call ...And Beyond

Zucked: Waking Up to the Facebook Catastrophe is an authoritative and frightening call to arms -- but I was disappointed that author Roger McNamee did not address some of the suggestions for remedies that I shared with him last June (posted as An Open Letter to Influencers Concerned About Facebook and Other Platforms).

Here are brief comments on this excellent book, and highlights of what I would add. Many recognize the problem with the advertising-based business model, but few seem to be serious about finding creative ways to solve it. It is not yet proven that my suggestions will work quite as I envision, but the deeper need is to get people thinking about finding and testing more win-win solutions. His book makes a powerful case for why this is urgently needed.

McNamee's urgent call to action

McNamee offers the perspective of a powerful Facebook and industry insider. A prominent tech VC, he was an early investor and mentor to Zuckerberg -- the advisor who suggested that he not sell to Yahoo, and who introduced him to Sandberg. He was alarmed in early-mid 2016 by early evidence of manipulation affecting the UK and US elections, but found that Zuckerberg and Sandberg were unwilling to recognize and act on his concerns. As he became more concerned, he joined with others to raise awareness of this issue and work to bring about needed change.

He provides a rich summary of how we got here, most of the issues we now face, and the many prominent voices for remedial action. He addresses the business issues and the broader questions of governance, democracy, and public policy. He tells us: “A dystopian technology future overran our lives before we were ready.” (As also quoted in the sharply favorable NY Times review.)

It's the business model, stupid!

McNamee adds his authoritative voice to the many observers who have concluded that the business model that serves advertisers to enable consumers to obtain "free" services distorts incentives, causing businesses to optimize for advertisers, not for users:
Without a change in incentives, we should expect the platforms to introduce new technologies that enhance their already-pervasive surveillance capabilities...the financial incentives of advertising business models guarantee that persuasion will always be the default goal of every design."
He goes on to suggest:
The most effective path would be for users to force change. Users have leverage...
The second path is government intervention. Normally I would approach regulation with extreme reluctance, but the ongoing damage to democracy, public health, privacy, and competition justifies extraordinary measures. The first step would be to address the design and bushiness model failures that make internet platforms vulnerable to exploitation. ...Facebook and Google have failed at self-regulation.
My suggestions on the business model, and related regulatory action

This is where I have novel suggestions -- outlined on my FairPayZone blog, and communicated to McNamee last June -- that have not gotten wide attention, and are ignored in Zucked. These are at two levels.

The auto emissions regulatory strategy. This is a simple, proven regulatory approach for forcing Facebook (and similar platforms) to shift from advertising-based revenue to user-based revenue. That would fundamentally shift incentives from user manipulation to user value.

If Facebook or other consumer platforms fail to move to do that voluntarily, this simple regulatory strategy could force that -- in a market-driven way. The government could simply mandate that X% of their revenue must come from their users -- with a timetable for gradually increasing X.  This is how auto emissions mandates work -- don't mandate how to fix things, just mandate a measurable result, and let the business figure out how best to achieve that. Since reverse-metered ads (with a specific credit against user fees) would count as a form of reader revenue, that would provide an immediate incentive for Facebook to provide such compensation -- and to begin developing other forms of user revenue. This strategy is outlined in Privacy AND Innovation ...NOT Oligopoly -- A Market Solution to a Market Problem.

The deeper shift to user revenue models. Creative strategies can enable Facebook (and other businesses) to shift from advertising revenue to become substantially user-funded. Zuckerberg has
thrown up his hands at finding a better way: "I don’t think the ad model is going to go away, because I think fundamentally, it’s important to have a service like this that everyone in the world can use, and the only way to do that is to have it be very cheap or free."

Who Should Pay the Piper for Facebook? (& the rest), explains this new business model architecture -- with a focus on how it can be applied to let Facebook be "cheap or free" for those who get limited value and have limited ability to pay, but still be paid for, at fair levels for those who get more value and who are willing and able to pay for that. This architecture, called FairPay, has gained recognition for operationalizing a solution that businesses can begin to apply now.
  • A reverse meter for ads and data. This FairPay architecture still allows for advertising to continue to defray the cost of service, but on a more selective, opt-in basis --  by applying a "reverse meter" that credits the value of user attention and data against each user's service fees -- at agreed upon terms and rates. That shifts the game from the advertiser being the customer of the platform, to to the advertiser being the customer of the user (facilitated by the platform). In that way advertising is carried only if done in a manner that is acceptable to the user. That aligns the incentives of the user, the advertiser, and the platform. Others have proposed similar directions, but I take it farther, in ways that Facebook could act on now.
  • A consumer-value-first model for user-revenue. Reverse metering is a good starting place for re-aligning incentives, but Facebook can go much deeper, to transform how its business operates.The simplest introduction to the transformative twist of the FairPay strategy is in my Techonomy article, Information Wants to be Free; Consumers May Want to Pay   (It has also been outlined in in Harvard Business Review, and more recently in the Journal of Revenue and Pricing Management.) The details will depend on context, and will need testing to fully develop and refine over time, but the principles are clear and well supported.

    This involves ways to mass-customize pricing of Facebook, to be "cheap or free" where appropriate, and to set customized fair prices for each user who obtain real value and can be enticed to pay for that. That is adaptive to individual usage and value-- and eliminates the risk of having to pay when the value actually obtained did not warrant that. That aligns incentives for transparency, trust, and co-creation of real value for each user. Behavioral economics has shown that people are willing to pay and will do so even voluntarily -- when they see good reason to help sustain the creation of value that they actually want and receive. We just need business models that understand and build on that.
Bottom line. Whatever the details, unless the Facebook shifts direction on its own to aggressively move in the direction of user payments -- which now seems unlikely -- regulatory pressure will be needed to force that (just as with auto emissions). A user revolt might force similar changes as well, but the problem is far too urgent to wait and see.

The broader call -- augmenting the wisdom of crowds

Shifting to a user-revenue-based business model will change incentives and drive significant progress to remedy many of the problems that McNamee and many others have raised. McNamee provides a wide-ranging overview of many of those problems and most of the initiatives that promise to help resolve them, but there, too, I offer suggestions that have not gained attention.

Most fundamental is the power of social media platforms to shape collective intelligence. Many have come to see that, while technology has great power to augment human intelligence, applied badly, it can have the opposite effect of making us more stupid. We need to steer hard for a more positive direction, now that we see how dangerous it is to take good results for granted, and how easily things can go bad. McNamee observes that "We...need to address these problems the old fashioned way, by talking to one another and finding common ground." Effective social media design can help us do that.

Another body of my work relates to how to design social media feeds and filtering algorithms to do just that, as explained in The Augmented Wisdom of Crowds:  Rate the Raters and Weight the Ratings:
  • The core issue is one of trust and authority -- it is hard to get consistent agreement in any broad population on who should be trusted or taken as an authority, no matter what their established credentials or reputation. Who decides what is fake news? What I suggested is that this is the same problem that has been made manageable by getting smarter about the wisdom of crowds -- much as Google's PageRank algorithm beat out Yahoo and AltaVista at making search engines effective at finding content that is relevant and useful.

    As explained further in that post, the essence of the method is to "rate the raters" -- and to weight those ratings accordingly. Working at Web scale, no rater's authority can be relied on without drawing on the judgement of the crowd. Furthermore, simple equal voting does not fully reflect the wisdom of the crowd -- there is deeper wisdom about those votes to be drawn from the crowd.

    Some of the crowd are more equal than others. Deciding who is more equal, and whose vote should be weighted more heavily can be determined by how people rate the raters -- and how those raters are rated -- and so on. Those ratings are not universal, but depend on the context: the domain and the community -- and the current intent or task of the user. Each of us wants to see what is most relevant, useful, appealing, or eye-opening -- for us -- and perhaps with different balances at different times. Computer intelligence can distill those recursive, context-dependent ratings, to augment human wisdom.
  • A major complicating issue is that of biased assimilation. The perverse truth seems to be that "balanced information may actually inflame extreme views." This is all too clear in the mirror worlds of pro-Trump and anti-Trump factions and their media favorites like Fox, CNN, and MSNBC. Each side thinks the other is unhinged or even evil, and layers a vicious cycle of distrust around anything they say. It seems one of the few promising counters to this vicious cycle is what Cass Sunstein referred to as surprising validators: people one usually gives credence to, but who suggest one's view on a particular issue might be wrong. An example of a surprising validator was the "Confession of an Anti-GMO Activist." This item is  readily identifiable as a "turncoat" opinion that might be influential for many, but smart algorithms can find similar items that are more subtle, and tied to less prominent people who may be known and respected by a particular user. There is an opportunity for electronic media services to exploit this insight that "what matters most may be not what is said, but who, exactly, is saying it."
If and when Facebook and other platforms really care about delivering value to their users (and our larger society), they will develop this kind of ability to augment the wisdom of the crowd. (Similar large-scale ranking technology is already proven in uses for advertising and Google search.) Our enlightened, democratic civilization will disintegrate or thrive, depending on whether they do that.

The facts of the facts. One important principle which I think McNamee misunderstands (as do many), is his critique that "To Facebook, facts are not absolute; they are a choice to be left initially to users and their friends but then magnified by algorithms to promote engagement." Yes, the problem is that the drive for engagement distorts our drive for the facts -- but the problem is not that "To Facebook, facts are not absolute." As I explain in The Tao of Fake Newsfacts are not absolute --we cannot rely on expert authorities to define absolute truth -- human knowledge emerges from an adaptive process of collective truth-seeking by successive approximation and the application of collective wisdom. It is always contingent on that, not absolute. That is how scholarship and science and democratic government work, that is what the psychology of cognition and knowledge demonstrates, and that is what effective social media can help all of us do better.

Other monopoly platform excesses - openness and interoperability

McNamee provides a good survey of many of the problems of monopoly (or oligopoly) power in the platforms, and some of the regulatory and antitrust remedies that are needed to restore the transparency, openness, and flexibility and market-driven incentives needed for healthy innovation. These include user ownership of their data and metadata, portability of the users' social graphs to promote competition, and audits and transparency of algorithms.

I have addressed similar issues, and go beyond McNamee's suggestions to emphasize the need for openness and interoperability of competing and complementary services -- see Architecting Our Platforms to Better Serve Us -- Augmenting and Modularizing the Algorithm. This draws on my early career experience watching antitrust regulatory actions relating to AT&T (in the Bell System days), IBM (in the mainframe era), and Microsoft (in the early Internet browser wars).

The wake up call

There are many prominent voices shouting wake up calls. See the partial list at the bottom of An Open Letter to Influencers Concerned About Facebook and Other Platforms, and MacNamee's Bibliographic Essay at the end of Zucked (excellent, except for the omission that I address here).

All are pointing in much the same direction. We all need to do what we can to focus the powers that be -- and the general population -- to understand and address this problem. The time to turn this rudderless ship around is dangerously short, and effective action to set a better direction and steer for it has barely begun. We have already sailed blithely into killer icebergs, and many more are ahead.

---
This is cross-posted from both of my blogs, FairPayZone.com and Reisman on User-Centered Media, which delve further into these issues.

Monday, January 14, 2019

The Real Crisis: The War to Save Democracy in 2020 Has Begun - Journalism Needs to Mobilize


This is one of the more complete of many prescriptions for journalists to manage this real crisis (and deflate the fake ones) -- but it is just another cry against the storm with no concrete plan for action.

The imminent crisis

The 2016 election in the US, similar problems around the world, "fake news," and disinformation have surfaced as crucial problems. Many are at work on solutions, but most will take time to be effective. We do not have that time.

In the US, and for the rest of the world, the most imminent threat is that Trump will use the press as he did in 2016 -- and still does. He still orchestrates a Trump-centric media circus. As Bruni points out, we need to restore meaningful conversation on the issues, whatever the policies at issue. 

Even most of those who support many of Trump's policies are dismayed at the dysfunction of this media circus (entertaining as it may be) -- this is not a partisan issue, but one all reasonable people can support.

Journalism needs to rally around best practices for containing this real and present danger now. Define them, follow them, and call out those who do not. To do that, leading journalists, publishers and J-schools should organize a Manhattan Project to unify and act now! If you do not do it right now, you may never have another chance.

Such a project should be inclusive, drawing in all who share the core values of intelligent discourse. 

Are you journalists, or cheerleaders (and profiteers) in a flame war?

Bruni's starter list

It is a long op-ed, well worth reading, and no doubt there are other important practices and tactics, but let's begin with some extracts from Bruni's op-ed (see the original for attribution of quotes):
“Pocahontas” won’t be lonely for long. …how much heed will we in the media pay to this stupidity? …That’s a specific question but also an overarching one — about the degree to which we’ll let him set the terms of the 2020 presidential campaign, about our appetite for antics versus substance, and about whether we’ll repeat the mistakes that we made in 2016 
Trump tortures us. Deliberately, yes, but I’m referring to the ways in which he keeps yanking our gaze his way.
“When you cover this as spectacle…what’s lost is context, perspective and depth. And when you cover this as spectacle, he is the star.” 
Trump was and is a perverse gift to the mainstream, establishment media, a magnet for eyeballs at a juncture when we were struggling economically and desperately needed one. Just present him as the high-wire act and car crash that he is; the audience gorges on it. But readers…[are] starved of information about the fraudulence of his supposed populism and the toll of his incompetence. And he wins. He doesn’t hate the media...He uses us.
Regarding their fitness for office, they [Trump and Clinton] were treated identically? In retrospect, that’s madness. It should have been in real time, too.
We need to do something else, too, which is to recognize that Trump now has an actual record in office and to discuss that with as much energy as we do his damned Twitter feed.
“Instead of covering Trump’s tweets on a live, breaking basis, just cover them in the last five minutes of a news show. They’re presidential statements, but we can balance them.”
We can also allow his challengers to talk about themselves as much as they do about him. …“It was deeply unfair… the question was always, ‘What’s your reaction to what Trump just said?,’ there’s no way to drive your own message.”
“It got to the point where it was one outrage after another, and we just moved on each time” …Instead, we should hold on to the most outrageous, unconscionable moments. We should pause there…. We can’t privilege the incremental over …the enduring. It lets Trump off the hook.
"…if you put enough experts on arguing… people will watch. And that’s what we’re doing with our politics. The media is not using their strength, their franchise, to elevate and illuminate the conversation. They’re just getting you all jazzed up about the game.”
But the lure of less demanding labors …is always there, especially because readers and viewers…reward it. What they lap up …is Trump the Baby…the Buffoon…the Bully… And that’s on them.
The real story of Trump isn’t his amorality and outrageousness. It’s Americans’ receptiveness to that. 
“Trump basically ran on blowing the whole thing up.…It’s critically important that we find ways to get at what it is people imagine government should be doing and…really look at what kind of leadership we need.”
A Manhattan Project for Journalism - the war to extinguish the flame war

When America became the "arsenal for democracy" in the battle against fascism, we mobilized for conventional warfare -- and with a massive Manhattan Project to change the game with an A-bomb. The best minds were assembled, tested many alternative strategies, and then focused the best resources in the world on what worked.

Trump has conquered the presidency with an artful flame war. Many have written very intelligently about the issues and strategies that Bruni raises. There is no silver bullet (or A-bomb), but there are a suite of strategies that promise to contain the nonsense -- but only if widely understood and practiced. No one person or organization has the knowledge or ability to do this alone. Bruni's points (and similar suggestions from many others) can be distilled, formalized and supplemented to provide a guide to best practices, both at high level, and in the guts of how journalism is practiced. Our best minds for journalism must come together and quickly define these best-practices, and then we must see to it that all understand them and work to enforce them.

If we have clear guidelines, we can call out and marginalize those who fan the flames - whether Trump and his supporters, or others.

Fair process is not partisan - the real challenge for "mainstream media"

Such a focus on process is not partisan, but simply a matter of a fairness to all citizens, and to the spirit of enlightened democracy that made America great. To the extent Trump or others (on either side of any issue) make responsible policy proposals and argue them responsibly, this would treat them fairly. To the extent they do not, it marginalizes them fairly.

Obviously our current government will not make this happen - no new "fairness doctrine" can be expected now. Journalists are uniquely positioned to step up to their responsibility. It must be a voluntary effort. Some prominent pundits and outlets will not cooperate, for political or business reasons. But a truly responsible "mainstream media" can work together to become a powerful force for reason. If we do not all hang together to fight the flame war, we will all hang separately.

Real Journalists of the World, Unite!

---
(If any broad effort to do this already exists, please let me know.)

(I am not a journalist, but one focus of my career has been on how technology can augment our collaborative intelligence. Journalism in this age is a form of such augmentation -- or more lately, de-augmentation.  I am ready to contribute to this effort as I can.)

Originally posted on my User-Centered Media blog.


Thursday, January 03, 2019

2019 New Year's Resolution: Let's Work Together to Invent a Better 2020!

My forecast for 2019: The best way to predict the future is to invent it -- let's work together on inventing a better 2020!

We face two over-arching and related challenges, one in the world of technology, and one in the larger world of enlightened democratic society.

At the broadest level, 2019 promises to be perhaps the worst and most traumatic year in recent American history. My point is not one of politics or policy (I bite my tongue), but of our basic processes of democratic society -- how we all work together to understand the world and make decisions. We now see all to well how much harm technology has done to that -- not by itself, but as an amplifier of the worst in us.

Within that world of technology, many have come to realize that we have taken a wrong turn in building vast and deeply influential infrastructures that are sustained by advertising. That perverts the profit incentive from creating value for we the people, to exploiting us to profit advertisers. That drive for engagement and targeting inherently conflicts with the creation of real value for users and society. We seem to not even be looking very hard for any solution beyond band-aids that barely alter 1) the perverse incentives of advertising, and 2) the failing zero-sum economics of artificial scarcity.

We seem to be at a loss for how to solve these problems at either level. I suggest that is simply a failure of will, imagination, and experimentation that we can all help rectify. Many prominent thought leaders have said much the same. I list some of them, and offer creative suggestions in An Open Letter to Influencers Concerned About Facebook and Other Platforms. I hope you will read it, as well as the related material it links to.

My suggestions are more specific, actionable, and practicalThat letter summarizes and links to ideas I have been developing for many years, but have taken on new urgency. They are well-supported, but as yet unproven in their full form. I can't be sure that my solutions will work, but there seems to be growing consensus that the problems are real, even if few have suggested any actionable path to solving them. (I have been a successful inventor and futurist for many decades. I have often been wrong about details of my answers, but have rarely have been far wrong about problems and issues. Very smart and well-informed people think I am on the right track here.)

But whether or not I am right about the solutions, we all have to make it a priority try to find, test, and refine the best solutions we can to confront these critical problems.

Still, few in technology, business, or government have turned from business as usual to rise to the urgent challenges we now face -- and even those who alert us to these problems seem to have few concrete strategies for effective action.

Please consider the urgency and importance of these issues at both levels, see if my suggestions or those of others resonate -- and add your voice in those directions -- or work to suggest better directions.

If we do not begin to make real progress in 2019, we may face a very dark 2020 and beyond.

If we do begin to turn this ship around, we can recharge the great promise of technology to augment our intellect and our society, and to create a new economics of abundance.

---
This is cross posted from both of my blogs, FairPayZone.com and Reisman on User-Centered Media, which delve further into these issues.

Friday, November 23, 2018

"As We Will Think" -- The Legacy of Ted Nelson, Original Visionary of the Web

From Nelson, As We Will Think (1972 version)
The vision of the Web in 1945

From a recent email from the Editor of The Atlantic:
In July 1945, Vannevar Bush, then the director of the U.S. Office of Scientific Research and Development—the military’s R&D lab, the predecessor to DARPA—published an essay in The Atlantic that would become one of the seminal pieces of technology literature of the 20th century.
Entitled “As We May Think,” the essay laid out a vision for a new kind of relationship between human and machine. Bush introduced an idea he called the memex: a sprawling, shared store of humankind’s knowledge that could be used for social good, not destruction. In the following years, preeminent technologists—including Doug Engelbart, whose work eventually led to the invention of the mouse, the word processor, and hyperlinks; and Sir Tim Berners-Lee, inventor of the World Wide Web—cited “As We May Think” as inspiration for their work.
The seminal re-visioning in the 1960's

It seems ironic that even the Atlantic seems to be neglecting Ted Nelson's role as an equally seminal visionary of the Web -- especially given that one of his early works was an explicit call to re-center on and realize Bush's vision, a work that plays off Bush's title as "As We Will Think."

I tweeted back to the Atlantic:
Some further tweets raised the question whether that was online somewhere, and it seems to be only in The Wayback Machine (archive.org), as a 1972 version -- and a poor copy at that, missing the original figures.

It happens that I have a better copy of the 1972 version, as well as another version that is labelled as being from 1968. So I am posting scans of both versions online (links below). I include some comments on provenance and on my recent email interchange with Nelson below (both of which lead me to believe the 1968 date is correct). But first...

Why Nelson matters 

A fuller explanation of  why Nelson matters is in my post from a few years ago, Digital Camelot - The Once and Future Web of Engelbart and Nelson, but here I caption its core message:

If you care about modern culture and how technology is shaping it, this is worth thinking about -- A powerful eulogy for where the Web might have gone, and still may someday, and the friendship of the two people most responsible for envisioning the Web*  --  Ted Nelson's eulogy for his friend Doug Engelbart, as reported by John Markoff in The Times -- with Nelson's inimitable flair.

As Markoff says:
Theodor Holm Nelson, who coined the term hypertext, has been a thorn in the side of the computing establishment for more than a half century. Last week, in an encomium to his friend Douglas Engelbart, he took his critique to Shakespearean levels. It deserves a wider audience. 
Dr. Engelbart and Ted Nelson became acquaintances at the dawn of the modern computing era. They had envisioned and invented the computing that we have come to take for granted.
I first encountered both of them in 1969, and what I saw set the direction for my life's work.  Engelbart gave "The Mother of All Demos" in 1968 (and I first saw him give a follow-up the next year, and read most of his work).  Nelson dreamed of hypertext and hypermedia, and wrote papers on what he called "hypertext" in the 'mid-60s and the highly influential Whole Earth Catalog of "Computer Lib / Dream Machines" in 1974.

As Nelson laments, both received a degree of recognition, but both were marginalized. Powerful as it may be, expediency took the Web in more limiting directions.

Their ideas remain profound and forward looking. Anyone who really cares about the future of media, intellect, and culture, and how information technology can augment that, should consider their work. Just because the Web took a turn to expediency in the past does not mean it will not realize its richer potential in the future. (One hint of that is noted in the next section [of that post].) ...

Nelson's insight

Ted's iconoclastic and visionary style is apparent from the opening of his "As We Will Think" (1968 version):
Bush was right, His famous article is, however, generally misinterpreted, for it has little to do with "information retrieval" as prosecuted today, Bush rejected indexing and discussed instead new forms of interwoven documents. 
It is possible that Bush's vision will be fulfilled substantially as he saw it, and that information retrieval systems of the kinds now popular will see less use than anticipated.
As the technological base has changed, we must recast his thesis slightly, and regard Bush's "memex" as three things: the personal presentation, editing and file console; a digital feeder network for the delivery of documents in full-text digital form; and new types of documents, or hypertexts, which are especially worth receiving and sending in this manner.
In addition, we also consider a likely design for specialist hypertexts, and discuss problems of their publication. 
BEATING AROUND THE BUSH
Twenty-three years ago, in a widely acclaimed article, Vannevar Bush made certain predictions about the way we of the future would handle written information (1). We are not yet doing so. Yet the Bush article is often cited as the historical beginning, or as a technological watershed, of the field of information retrieval. It is frequently cited without interpretation (2,3). Although some commentators have said its predictions were improbable (4), in general its precepts have been ignored by acclamation...
In hindsight, it is obvious that Ted was right about Bush's vision. The memex pre-saged wonders far beyond the mundane notion of "information retrieval" as generally understood in the 1960s (even if not all of Bush, Engelbart and Nelson's visions have been embodied in the Web).

For an interesting update that theme, see this 2016 Quartz article and its reference to Werner Herzog's interview of Ted for his film Lo and Behold, and a short video of Ted expanding on what he spoke of. Both provide a nice live demos of the "parallel textface," much as shown in the above image from Ted's 1972 article. This also explains Ted's ideas of "transclusion" of elements from one work into another, as a rich kind of mashup that retains the identity of the original elements.  He explains how that can support creator rights to what is linked in, and micropayment-based payment/compensation models.* I have often heard people speculate about some of these exciting ideas, thinking they were new (and sometimes that they invented them). Few realize that Ted described all this in the '60s and '70s,

Those trying to invent this "deeply intertwingled" future might want to stand on Ted's shoulders. Ted may not have had the entrepreneurial genius of Steve Jobs, but his inventive vision is second to none.

The Atlantic might want to talk to him...

---
1968? really? -- it seems yes

Nelson actually wrote previously about his ideas for hypertext (in the mid 1960s), so the exact date of this particular paper may not be of great importance, but its earliest provenance is a be a bit of a puzzle.

I recently corresponded with Ted by email, and he was intrigued by these finds -- happy to have the full 1972 version and puzzled by the "1968" version. He said he did not recall a formal publication from that date, but that he might have provided a version at the ACS Annual Meeting then.

Both papers are from my hard copy file, just as they appear in the scans now posted (with the hand annotations apparently being mine, from when I first read them). I believe I had ordered them from my company library and that the label "ACS Annual Meeting 1968" was the citation information with which I ordered that copy. (I presumed that referred to the American Chemical Society, which seemed a bit far afield, but Ted did have a wide range.) So it seemed to remain a puzzle.

However as I was drafting this post, I noticed that the 1968 version says "Twenty-three years ago..." while the 1972 version says "Twenty-seven years ago..." That would seem to be compelling evidence that my "1968" version actually was from that year.

To add more personal history, I had the pleasure of meeting with Ted in 1970 to explore assisting in an experimental hypertext implementation under Claude Kagan's direction, as part of my masters degree fellowship work at the AT&T Western Electric Research Center. That project did not materialize, but chatting with Ted about hypertext was one of the most memorable hours of my career.

---
Early works by Ted Nelson from my collection

The following are items by Ted that may not to be generally available online. I collected these from 1969 onward, and plan to post scans of all them as I get time (after checking whether comparable copies are already accessible elsewhere).
  • As We Will Think ("ACS Annual Meeting 1968" version
    (unable to confirm citation and date)
  • As We Will Think ("Online 72 Conference Proceedings" version 
    (fuller than the scan at archive.org, includes original figures/photos)
  • “Hypertext Editing System,” published by Brown University on 5/6/69 for the Spring Joint Computer Conference, 5/14-16/69
    (My first exposure to hypertext. I clicked a link and saw the future. It was at the IBM booth running on a "mid-sized" IBM 360/50 mainframe with a 2250 vector graphics workstation equipped with a light-pen. Coincidentally, I knew Andy van Dam and some of the developers from my time at Brown the years just before.)
  • Short Computer Lib “$5 First Edition” ©’73, on typewriter paper hand-duplexed, 12 pages including Dream Machines flip-side.
  • A File Structure for the Changing and the Indeterminate, ACM National Conference 1965
  • Xanadu Draft Brochure, 27 November 1969
  • Computer Decisions 9/70  -- No More Teacher’s Dirty Looks
  • Hypertext Note 0-9, various dates in ‘67
  • Decision/Creativity Systems dated 19 July 1970
  • Hypertexts 20 Mar 70
  • Getting it out of our system, in Schechter, ‘67
  • A 14 December 1970 PDP10 teletype printout of Ted's “final report” for Claude Kagan of Western Electric (maybe incomplete with related fragments) -- as noted above, I met with Ted around that time to discuss assisting in this project while in my master's degree fellowship program. (I suspect this was not distributed beyond Ted, Claude, and me.)
(Copies will also be placed on Google Drive.)

---
*An innovation of my own is relevant to this use of micropayments. Micropayments have a long history of enthusiasm and failure. The problem is that micropayments add up to macropayments, resulting in the shock of a nasty surprise when the bill is presented, or the fear of such a surprise. My short answer to how to fix that is to make the micro-payments variable, including some form of volume discounts and price caps, and to provide forgiveness when the value received is not satisfactory. Details of how do that are in this recent post on my other blog: "The Case Against Micropayments" -- From Fear and Surprise to The Comfy Chair.

Historical Clarification:  I should note that my original tweet, above was imprecise in saying "bringing Bush to the attention of those you name." I gather that Engelbart arrived at the basic idea of hypertext independently, and only later became aware of Ted's work. However my understanding is the Tim Berner-Lee was influenced by Ted, as referenced in his proposal for the WWW.

Wednesday, October 10, 2018

In the War on Fake News, All of Us are Soldiers, Already!

This is intended as a supplement to my posts "A Cognitive Immune System for Social Media -- Developing Systemic Resistance to Fake News" and "The Augmented Wisdom of Crowds: Rate the Raters and Weight the Ratings." (But hopefully this stands on its own as well).Maybe this can make a clearer point of why the methods I propose are powerful and badly needed...
---

A NY Times article titled "Soldiers in Facebook’s War on Fake News Are Feeling Overrun" provides a simple context for showing how I propose to use information already available from all of us, on what is valid and what is fake.

The Times article describes a fact checking organization that works with Facebook in the Philippines (emphasis added):
On the front lines in the war over misinformation, Rappler is overmatched and outgunned - and that could be a worrying indicator of Facebook’s effort to curb the global problem by tapping fact-checking organizations around the world.
...it goes on to describe what I suggest is the heart of the issue:
When its fact checkers determine that a story is false, Facebook pushes it down on users’ News Feeds in favor of other material. Facebook does not delete the content, because it does not want to be seen as censoring free speech, and says demoting false content sharply reduces abuse. Still, falsehoods can resurface or become popular again.
The problem is that the fire hose of fake news is too fast and furious, and too diverse, for any specialized team of fact-checkers to keep up with it. Plus, the damage is done by the time they do identify the fakes and begin to demote them.

But we are all fact checking to some degree without even realizing it. We are all citizen-soldiers. Some do it better than others.

The trick is to draw out all of the signals we provide, in real time -- and use our knowledge of which users' signals are reliable -- to get smarter about what gets pushed down and what gets favored in our feeds. That can serve as a systemic cognitive immune system -- one based on rating the raters and weighting the ratings.

We are all rating all of our news, all of the time, whether implicitly or explicitly, without making any special effort:

  • When we read, "like," comment, or share an item, we provide implicit signals of interest, and perhaps approval.
  • When we comment or share an item, we provide explicit comments that may offer supplementary signals of approval or disapproval.
  • When we ignore an item, we provide a signal of disinterest (and perhaps disapproval).
  • When we return to other activity after viewing an item, the time elapsed signals our level of attention and interest.
Individually, inferences from the more implicit signals may be erratic and low in meaning. But when we have signals from thousands of people, the aggregate becomes meaningful. Trends can be seen quickly. (Facebook already uses such signals to target its ads -- that is how they makes so much money).

But simply adding all these signals can be misleading. 
  • Fake news can quickly spread through groups who are biased (including people or bots who have an ulterior interest in promoting an item) or are simply uncritical and easily inflamed -- making such an item appear to be popular.
  • But our platforms can learn who has which biases, and who is uncritical and easily inflamed.
  • They can learn who is respected within and beyond their narrow factions, and who is not, who is a shill (or a malicious bot) and who is not.
  • They can use this "rating" of the raters to weight their ratings higher or lower.
Done at scale, that can quickly provide probabilistically strong signals that an item is fake or misleading or just low quality. Those signals can enable the platform to demote low quality content and promote high quality content. 

To expand just a bit:
  • Facebook can use outside fact checkers, and can build AI to automatically signal items that seem questionable as one part of its defense.
  • But even without any information at all about the content and meaning of an item, it can make realtime inferences about its quality based on how users react to it.
  • If most of the amplification is from users known to be malicious, biased, or unreliable it can downrank items accordingly
  • It can test that downranking by monitoring further activity.
  • It might even enlist "testers" by promoting a questionable item to users known to be reliable, open, and critical thinkers -- and may even let some generally reliable users to self-select as validators (being careful not to overload them).
  • By being open-ended in this way, such downranking is not censorship -- it is merely a self-regulating learning process that works at Internet scale, on Internet time.
That is how we can augment the wisdom of the crowd -- in real time, with increasing reliability as we learn. That is how we build a cognitive immune system (as my other posts explain further).

This strategy is not new or unproven. It is is the core of Google's wildly successful PageRank algorithm for finding useful search results. And (as I have noted before), it was recently reported that Facebook is now beginning to do a similar, but apparently still primitive form of rating the trustworthiness of its users to try to identify fake news -- they track who spreads fake news and who reports abuse truthfully or deceitfully.* 

What I propose is that we take this much farther, and move rapidly to make it central to our filtering strategies for social media -- and more broadly. An all out effort to do that quickly may be our last, best hope for enlightened democracy.

---
Please see my other posts for more.
----
(*More background from Facebook on their current efforts was cited in the Times article: Hard Questions: What is Facebook Doing to Protect Election Security?

[Update 10/12:] A subsequent Times article by Sheera Frenkel, adds perspective on the scope and pace of the problem -- and the difficulty in definitively identifying items as fakes that can rightly be censored "because of the blurry lines between free speech and disinformation" -- but such questionable items can be down-ranked.

Monday, October 08, 2018

A Cognitive Immune System for Social Media -- Developing Systemic Resistance to Fake News

To counter the spread of fake news, it's more important to manage and filter its spread than to try to interdict its creation -- or to try to inoculate people against its influence. 

A recent NY Times article on their inside look at Facebook's election "war room" highlights the problem, quoting cybersecurity expert Priscilla Moriuchi:
If you look at the way that foreign influence operations have changed these last two years, their focus isn’t really on propagating fake news anymore. “It’s on augmenting stories already out there which speak to hyperpartisan audiences.”
That is why much of the growing effort to respond to the newly recognized crisis of fake news, Russian disinformation, and other forms of disruption in our social media fails to address the core of the problem. We cannot solve the problem by trying to close our systems off from fake news, nor can we expect to radically change people's natural tendency toward cognitive bias. The core problem is that our social media platforms lack an effective "cognitive immune system" that can resist our own tendency to spread the "cognitive pathogens" that are endemic in our social information environment.

Consider how living organisms have evolved to contain infections. We did that not by developing impermeable skins that could be counted on to keep all infections out, nor by making all of our cells so invulnerable that they can resist whatever infectious agents may unpredictably appear.

We have powerfully complemented what we can do in those ways by developing a richly nuanced internal immune system that is deeply embedded throughout our tissues. That immune system uses emergent processes at a system-wide level -- to first learn to identify dangerous agents of disease, and then to learn how to resist their replication and virulence as they try to spread through our system.

The problem is that our social media lack an effective "cognitive immune system" of this kind. 

In fact many of our social media platforms are designed by the businesses that operate them to maximize engagement so they can sell ads. In doing so, they have learned that spreading incendiary disinformation that makes people angry and upset, polarizing them into warring factions, increases their engagement. As a result, these platforms actually learn to spread disease rather than to build immunity. They learn to exploit the fact that people have cognitive biases that make them want to be cocooned in comfortable filter bubbles and feel-good echo-chambers, and to ignore and refute anything that might challenge beliefs that are wrong but comfortable. They work against our human values, not for them.

What are we doing about it? Are we addressing this deep issue of immunity, or are we just putting on band-aids and hoping we can teach people to be smarter? (As a related issue, are we addressing the underlying issue of business model incentives?) Current efforts seem to be focused on measures at the end-points of our social media systems:
  • Stopping disinformation at the source. We certainly should apply band-aids to prevent bad-actors from injecting our media with news, posts, and other items that are intentionally false and dishonest. Of course we should seek to block such items and those who inject them. Band-aids are useful when we find an open wound that germs are gaining entry through. But band-aids are still just band-aids.
  • Making it easier for individuals to recognize when items they receive may be harmful because they are not what they seem. We certainly should provide "immune markers" in the form of consumer-reports-like ratings of items and of the publishers or people who produce them (as many are seeking to do). Making such markers visible to users can help prime them to be more skeptical, and perhaps apply more critical thinking -- much like applying an antiseptic. But that depends on the willingness of users to pay attention to such markers and apply the antiseptic. There is good reason to doubt that will have more than modest effectiveness, given people's natural laziness and instinct for thinking fast rather than slow. (Many social media users "like" items based only on click-bait headlines that are often inflammatory and misleading, without even reading the item -- and that is often enough to cause those items to spread massively.)
These end-point measures are helpful and should be aggressively pursued, but we need to urgently pursue a more systemic strategy of defense. We need to address the problem of dissemination and amplification itself. We need to be much smarter about what gets spread -- from whom, to whom, and why.

Doing that means getting deep into the guts of how our media are filtered and disseminated, step by step, through the "viral" amplification layers of the media systems that connect us. That means integrating a cognitive immune system into the core of our social media platforms. Getting the platform owners to buy in to that will be challenging, but it is the only effective remedy.

Building a cognitive immune system -- the biological parallel

This perspective comes out of work I have been doing for decades, and have written about on this blog (and in a patent filing since released into the public domain). That work centers on ideas for augmenting human intelligence with computer support. More specifically, it is centers on augmenting the wisdom of crowds. It is based on the idea the our wisdom is not the simple result of a majority vote -- but results from an emergent process that applies smart filters that rate the raters and weight the ratings. That provides a way to learn which votes should be more equal than others (in a way that is democratic and egalitarian, but also merit-based). This approach is explained in the posts listed below. It extends an approach that has been developing for centuries.

Supportive of those perspectives, I recently turned to some work on biological immunity that uses the term "cognitive immune system." That work highlight the rich informational aspects of actual immune systems, as a model for understanding how these systems work at a systems level. As noted in one paper (see longer extract below*), biological immune systems are "cognitive, adaptive, fault-tolerant, and fuzzy conceptually." I have only begun to think about the parallels here, but it is apparent that the system architecture I have proposed in my other posts is at least broadly parallel, being also "cognitive, adaptive, fault-tolerant, and fuzzy conceptually." (Of course being "fuzzy conceptually" makes it not the easiest thing to explain and build, but when that is the inherent nature of the problem, it may also necessarily be the essential nature of the solution -- just as it is for biological immune systems.)

An important aspect of this being "fuzzy conceptually," is what I call The Tao of Truth. We can't definitively declare good-faith "speech" as "fake" or "false" in the abstract. Validity is "fuzzy" because it depends on context and interpretation. ("Fuzzy logic" recognizes that in the real world, it is often the case that facts are not entirely true or false but, rather, have degrees of truth.)  That is why only the clearest cases of disinformation can be safely cut off at the source. But we can develop a robust system for ranking the probable (fuzzy) value and truthfulness of speech, revising those rankings, and using that to decide how to share it with whom. For practical purposes, truth is a filtering process, and we can get much smarter about how we apply our collective intelligence to do our filtering. It seems the concepts of "danger" and "self/not-self" in our immune systems have a similarly fuzzy Tao -- many denizens of our microbiome that are not "self" are beneficial to us, and our immune systems have learned that we live better with them inside of us.

My proposals

Details of the architecture I have proposed for a cognitive immune system -- and the need for it -- are here:
  • The Tao of Fake News – the essential need for fuzziness in our logic: the inherent limits of experts, moderators, and rating agencies – and the need for augmenting the wisdom of the crowd (as essential to maintaining the intellectual openness of our democratic/enlightenment values).
(These works did not explicitly address the parallels with biological cognitive immune systems -- exploring those parallels might well lead to improvements on these strategies.)

To those without a background in the technology of modern information platforms, this brief outline may seem abstract and unclear. But as noted in these more detailed posts, these methods are a generalization of methods used by Google (in its PageRank algorithm) to do highly context-relevant filtering of search results using a similar rate the raters and weight the ratings strategy. (That is also "cognitive, adaptive, fault-tolerant, and fuzzy conceptually.") These methods not simple, but they are little stretch from the current computational methods of search engines, or from the ad targeting methods already well-developed by Facebook and others. They can be readily applied -- if the platforms can be motivated to do so.

Broader issues of support for our cognitive immune system

The issue of motivation to do this is crucial. For the kind of cognitive immune system I propose to be effective, it must be built deeply into the guts of our social media platforms (whether directly, or via APIs). As noted above, getting incumbent platforms to shift their business models to align their internal incentives with that need will be challenging. But I suggest it need not be as difficult as it might seem.
A related non-technical issue that many have noted is the need for education of citizens 1) in critical thinking, and 2) in the civics of our democracy. Both seem to have been badly neglected in recent decades. Aggressively remedying that is important, to help inoculate users from disinformation and sloppy thinking -- but that will have limited effectiveness unless we alter the overwhelmingly fast dynamics of our information flows (with the cognitive immune system suggested here) -- to help make us smarter, not dumber in the face of this deluge of information.

---
[Update 10/12:] A subsequent Times article by Sheera Frenkel, adds perspective on the scope and pace of the problem -- and the difficulty in definitively identifying items as fakes that can rightly be censored "because of the blurry lines between free speech and disinformation" -- but such questionable items can be down-ranked.
-----
*Background on our Immune Systems -- from the introduction to the paper mentioned above, "A Cognitive Computational Model Inspired by the Immune System Response" (emphasis added):
The immune system (IS) is by nature a highly distributed, adaptive, and self-organized system that maintains a memory of past encounters and has the ability to continuously learn about new encounters; the immune system as a whole is being interpreted as an intelligent agent. The immune system, along with the central nervous system, represents the most complex biological system in nature [1]. This paper is an attempt to investigate and analyze the immune system response (ISR) in an effort to build a framework inspired by ISR. This framework maintains the same features as the IS itself; it is cognitive, adaptive, fault-tolerant, and fuzzy conceptually. The paper sets three phases for ISR operating sequentially, namely, “recognition,” “decision making,” and “execution,” in addition to another phase operating in parallel which is “maturation.” This paper approaches these phases in detail as a component based architecture model. Then, we will introduce a proposal for a new hybrid and cognitive architecture inspired by ISR. The framework could be used in interdisciplinary systems as manifested in the ISR simulation. Then we will be moving to a high level architecture for the complex adaptive system. IS, as a first class adaptive system, operates on the body context (antigens, body cells, and immune cells). ISR matured over time and enriched its own knowledge base, while neither the context nor the knowledge base is constant, so the response will not be exactly the same even when the immune system encounters the same antigen. A wide range of disciplines is to be discussed in the paper, including artificial intelligence, computational immunology, artificial immune system, and distributed complex adaptive systems. Immunology is one of the fields in biology where the roles of computational and mathematical modeling and analysis were recognized...
The paper supposes that immune system is a cognitive system; IS has beliefs, knowledge, and view about concrete things in our bodies [created out of an ongoing emergent process], which gives IS the ability to abstract, filter, and classify the information to take the proper decisions.

Monday, August 27, 2018

The Tao of Fake News

We are smarter than this!

Everyone with any sense sees "fake news" disinformation campaigns as an existential threat to "truth, justice, and the American Way," but we keep looking for a Superman to sort out what is true and what is fake. A moment's reflection shows that, no Virginia, there is no SuperArbiter of truth. No matter who you choose to check or rate content, there will always be more or less legitimate claims of improper bias.
  • We can't rely on "experts" or "moderators" or any kind of "Consumer Reports" of news. We certainly can't rely on the Likes of the Crowd, a simplistic form of the Wisdom of the Crowd that is too prone to "The Madness of Crowds." 
  • But we can Augment the Wisdom of the Crowd.
  • We can't definitively declare good-faith "speech" as "fake" or "false." 
  • But we can develop a robust system for ranking the probable value and truthfulness of speech, revising those rankings, and using that to decide how to share it with whom.
For practical purposes, truth is a filtering process, and we can get much smarter about how we apply our collective intelligence to do our filtering.

The Tao of Fake News, Truth, and Meaning

Truth is a process. Truth is complex. Truth depends on interpretation and context. Meaning depends on who is saying something, to whom, and why (as Humpty-Dumpty observed). The truth in Rashomon is different for each of the characters. Truth is often very hard for individuals (even "experts") to parse.

Truth is a process, because there is no practical way to ensure that people speak the truth, nor any easy way to determine if they have spoken the truth. Many look to the idea of flagging fake news sources, but who judges, on what basis and what aspects? (A recent NeimanLab assessment of NewsGuard's attempt to do this shows how open to dispute even well-funded, highly professional efforts to do that are.)

Truth is a filtering process: How do we filter true speech from false speech? Over centuries we have come to rely on juries and similar kinds of panels, working in a structured process to draw out and "augment" the collective wisdom of a small crowd. In the sciences, we have a more richly structured process for augmenting the collective wisdom of a large crowd of scientists (and their experiments), informally weighing the authority of each member of the crowd -- and avoiding over-reliance on a few "experts." Our truths are not black and white, absolute, and eternal -- they are contingent, nuanced, and tentative -- but this Tao of truth has served us well.

It is now urgent that our methods for augmenting and filtering our collective wisdom be enhanced. We need to apply computer-mediated collaboration to apply a similar augmented wisdom of the crowd at Internet scale and speed. We can make quick initial assessments, then adapt, grow, and refine our assessments of what is true, in what way, and with regard to what.

Filtering truth -- networks, context, and community

If our goal is to exclude all false and harmful material, we will fail. The nature of truth, and of human values, is too complex. We can exclude the most obviously pernicious frauds -- but for good-faith speech from humans in a free society, we must rely on a more nuanced kind of wisdom.

Our media filter what we see. Now the filters in our dominant social media are controlled by a few corporations motivated to maximize ad revenue by maximizing engagement. They work to serve the advertisers that are their customers, not we users (who now are really their product). We need to get them to change how the filters operate, to maximize value to their users.

We need filters to be tuned to the real value of speech as communication from one person to other people.  Most people want the "firehose" of items on the Internet to be filtered in some way, but just how may vary. Our filters need to be responsive to the desires of the recipients. Partisans may like the comfort of their distorting filter bubbles, but most people will want at least some level of value, quality, and reality, at least some of the time. We can reinforce that by doing well at it.

There is also the fact that people live in communities. Standards for what is truthful and valuable vary from community to community -- and communities and people change over time. This is clearer than ever, now that our social networks are global.

Freedom of speech requires that objectionable speech be speak-able, with very narrow exceptions. The issue is who hears that speech, and what control do they have over what they hear. A related issues is when do third parties have a right to influence those listener choices, and how to keep that intrusive hand as light as possible. Some may think we should never see a swastika or a heresy, but who has the right to draw such lines for everyone in every context?

We cannot shut off objectionable speech, but we can get smarter about managing how it spreads. 

To see this more clearly, consider our human social network as a system of collective intelligence, one that informs an operational definition of truth. Whether at the level of a single social network like Facebook, or all of our information networks, we have three kinds of elements:
  • Sources of information items (publishers, ordinary people, organizations, and even bots) 
  • Recipients of information items  
  • Distribution systems that connect the sources and recipients using filters and presentation service that determine what we see and how we see it (including optional indicators of likely truthfulness, bias, and quality).
Controlling truth at the source may, at first, seem the simple solution, but requires a level of control of speech that is inconsistent with a free society. Letting misinformation and harmful content enter our networks may seem unacceptable, but (with narrow exceptions) censorship is just not a good solution.

Some question whether it is enough to "downrank" items in our feeds (not deleted, but less likely to be presented to us), but what better option do we have than to do that wisely? The best we can reasonably do is manage the spread of low quality and harmful information in a way that is respectful of the rights of both sources and recipients, to limit harm and maximize value.*

How can we do that, and who should control it? We, the people, should control it ourselves (with some limited oversight and support).  Here is how.

Getting smarter -- The Augmented Wisdom of Crowds

Neither automation nor human intelligence alone is up to the scale and dynamics of the problem.  We need a computer-augmented approach to managing the wisdom of the crowd -- as embodied in our filters, and controlled by us. That will pull in all of the human intelligence we can access, and apply algorithms and machine learning (with human oversight) to refine and apply it. The good news is that we have the technology to do that. It is just a matter of the will to develop and apply it.

My previous post outlines a practical strategy for doing that -- "The Augmented Wisdom of Crowds: Rate the Raters and Weight the Ratings." Google has already shown how powerful a parallel form of this strategy can be to filter which search results should be presented to whom-- on Internet scale. My proposal is to broaden these methods to filter what our our social media present to us.

The method is one of considering all available "signals" in the network and learning how to use them to inform our filtering process. The core of the information filtering process -- that can be used for all kinds of media, including our social media -- is to use all the data signals that our media systems have about our activity. We can consider activity patterns across these three dimensions:
  • Information items (content of any kind, including news items, personal updates, comments/replies, likes, and shares/retweets).
  • Participants (and communities and sub-communities of participants), who can serve as both sources and recipients of items (and of items about other items)
  • Subject and task domains (and sub-domains) that give important context to information items and participants.
We can apply this data with the understanding that any item or participant can be rated, and any item can contain one or more ratings (implicit or explicit) of other items and/or participants. The trick is to tease out and make sense of all of these interrelated ratings and relationships. To be smart about that, we must recognize that not all ratings as equal, so we "rate the raters, and weight the ratings" (using any data that signals a rating). We take that to multiple levels -- my reputational authority depends not only on the reputational authority of those who rate me, but on those who rate them (and so on).

This may seem very complicated (and at scale, it is), but Google proved the power of such algorithms to determine which search results are relevant to a user's query (at mind-boggling scale and speed). Their PageRank algorithm considers what pages link to a given page to assess the imputed reputational authority of that page -- with weightings based on the imputed authority of the pages that link to it (again to multiple levels). Facebook uses similarly sophisticated algorithms to determine what ads should be targeted to whom -- tracking and matching user interests, similarities, and communities and matching that with information on their response to similar ads.

In some encouraging news, it was recently reported that Facebook is now also doing a very primitive form of rating the trustworthiness of its users to try to identify fake news -- they track who spreads fake news and who reports abuse truthfully or deceitfully. What I propose is that we take this much farther, and make it central to our filtering strategies for social media and more broadly.

With this strategy, we can improve our media filters to better meet our needs, as follows:
  • Track explicit and implicit signals to determine authority and truthfulness -- both of the speakers (participants) and of the things they say (items) -- drawing on the wisdom of those who hear and repeat it (or otherwise signal how they value it).
  • Do similar tracking to understand the desires and critical thinking skills of each of the recipients
  • Rate the raters (all of us!) -- and weight the votes to favor those with better ratings. Do that n-levels deep (much as Google does).
  • Let the users signal what levels and types of filtering they want. Provide defaults and options to accommodate users desiring different balances of ease or of fine control and reporting. Let users change that as they desire, depending on their wish to relax, to do focused critical thinking, or to open up to serendipity.
  • Provide transparency and auditability -- to each user (and to independent auditors) -- as to what is filtered for them and how.**
  • Open the filtering mechanisms to independent providers, to spur innovation in a competitive marketplace in filtering algorithms for users to choose from.
That is the best broad solution that we can apply. As we get good at it we will be amazed at how effective it can be. But given the catastrophic folly of where have have let this get to...

First, do no harm!

Most urgently, we need to change the incentives of our filters to do good, not harm. At present, our filters are pouring gasoline on the fires (even as their corporate owners claim to be trying to put them out). As explained in a recent HBR article, "current digital advertising business models incentivize the spread of false news." That article explains the insidious problem of the ad model for paying for services (others have called it "the original sin of the Web") and offers some sensible remedies.  

I have proposed more innovative approaches to better-aligning business models -- and to using a light-handed, market-driven, regulatory approach to mandate doing that -- in "An Open Letter to Influencers Concerned About Facebook and Other Platforms."

We have learned that the Internet has all the messiness of humanity and its truths. We are facing a Pearl Harbor of a thousand pin-pricks that is rapidly escalating. We must mobilize onto a war footing now, to halt that before it is too late.
  • First we need to understand the nature and urgency of this threat to democracy, 
  • Then we must move on both short and longer time horizons to slow and then reverse the threat. 
The Tao of fake news contains its opposite, the Tao of Augmented Wisdom. If we seek that, the result will be not only to manage fake news, but to be smarter in our collective wisdom than we can now imagine.

Related posts:
---
*Of course some information items will be clearly malicious, coming from fraudulent human accounts or bots -- and shutting some of that off at the source is feasible and desirable. But much of the spread of "fake news" (malicious or not) is from real people acting in good faith, in accord with their understanding and beliefs. We cannot escape that non-binary nature of human reality, and must come to terms with our world in nuanced shades of gray. But we can get very sophisticated at distinguishing when news is spread by participants who are usually reliable from when it is spread by those who have established a reputation for being credulous, biased, or malicious.

**The usual concern with transparency is that if the algorithms are known, then bad-actors will game them. That is a valid concern, and some have suggested that even if the how of the filtering algorithm is secret, we should be able to see and audit the why for a given result.  But to the extent that there is an open market in filtering methods (and in countermeasures to disinformation), and our filters vary from user to user and time to time, there will be so much variability in the algorithms that it will be hard to game them effectively.

---
[Update 8/30:]  Giuliani and The Tao of Truth 

To indulge in some timely musing, the Tao of Truth gives a perspective on the widely noted recent public statement that "truth isn't truth." At the level of the Tao, we can say that "truth is/isn't truth," or more precisely, "truth is/isn't Truth" (with one capital T). That is the level at which we understand truth to be a process in which the question "what is truth?" depends on what we mean, at what level, in what context, with what assurance -- and how far we are in that process. We as a society have developed a broadly shared expectation of how that process should work. But as the process does its never-ending work, there are no absolutes -- only more or less strong evidence, reasoning, and consensus about what we believe the relevant truth to be. (That, of course is an Enlightenment social perspective, and some disagree with this very process, and instead favor a more absolute and authoritarian variation. Perhaps most fundamentally, we are now in a reactionary time in which our prevailing process for truth is being prominently questioned. The hope here is that continuing development of a free, open, and wise process prevails over return to a closed, authoritarian one -- and prevails over the loss of any consensus at all.

[Update 10/12:] A Times article by Sheera Frenkel, adds perspective on the scope and pace of the problem -- and the difficulty in definitively identifying items as fakes that can be censored "because of the blurry lines between free speech and disinformation" -- but such questionable items can be down-ranked.