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.

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[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.
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*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.

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