Don't Be a Troll, Be a Wizard!
A vision for how scientific knowledge engineering could support data-driven policy development. This is a preliminary high-level strategic document to develop such tools to support efforts such as 314 Action.
By Gully A. Burns
“Trolls were large monsters of limited intellect. They were strong and vicious, but they could not endure sunlight”
Technologically, we live in interesting times. On the one hand, social media technology drives political discourse into polarized shouting matches. Astroturfing bots contort the political landscape by pushing false narratives on Twitter with incendiary, ill-informed talking points. The ease of web-publishing makes it relatively easy to drown out informative scientific work by spreading misinformation in coordinated online media campaigns.
But on the other hand, advances in information science drive public engagement in science. Citizen scientist projects permit laypeople to contribute directly to research. Massive Open Online Courses (MOOCs) provide pedagogical support for technically demanding subjects to more communitites than ever before. The information infrastructure of science itself is evolving to change and accelerate the path towards discovery.
These two aspects are sharply opposed, especially when it comes to online discussions of policy. The first approach is based on misinformation, manipulation, provocation, and storytelling. These approaches are generally developed by unscrupulous operators attempting to control a particular public narrative through any means necessary. Let’s call the instigators of such methods ‘Trolls’. The second approach is based on hard work, research, a nuanced view of reality in the service of the pursuit of scientific truth. This less-popular, more long-term (and therefore more powerful) approach requires diligence, honesty, intelligence, and patience. To emphasize the contrast with the formerly-mentioned misbeggoten misinformationists, I here propose that we call people pursuing this endeavor ‘Wizards’. Thus, somewhat, in the spirit of pure geekiness, we frame the argument as a perrenial war of political storytelling between two factions: wizards and trolls.
Now, the mission statement of the 314 Action nonprofit group, reveals them to be clearly on the Wizards’ team. Their primary goal to empower scientific information to carry further within the process of setting policy, either by electing scientifically-trained politicians or by empowering data-driven policy and scientific research within society.
Our work in scientific knowledge engineering (and, more broadly, in artificial intelligence) directly supports 314 Action’s vision by developing technology to be used to improve access to complex scientific knowledge. Moreover, the people 314 Action are seeking to introduce into public life would be trained to think scientifically and to adopt pragmatic, data-driven methodologies. Put simply, if 314 Action provides the wizards, then we can provide the spells.
I elaborate further below.
A Challenge Problem: the Argument over Climate Change
Once of the key issues raging in public policy discourse discussions in the United States is climate change. Debate in this area largely centeres around the following question:
Is the planet warming up because of increased CO2 in the atmosphere from human activity and energy use?
This is a contentious question despite a groundswell of public support amongst progressives, combined with a broad consensus over the majority of scientists working in the discipline. Most researchers either explicitly or implicitly agree that this is indeed the case: the global temperature is increasing directly because of increased levels of greenhouse gases in the atmosphere (most likely caused by human energy use). Broad literature reviews generally confirm this point of view and even large scale organizations that enjoy widespread public trust such as NASA agree full-throatedly that climate change poses a serious threat to humanity as a whole.
But there is also a powerful counter-movement at play within conservative circles: climate skepticism. Proponents of this position claim that the science is not settled, that potential risks of climate change to humanity are being unnecessary amplified by liberals for political gain and that numerous details in the published account don’t add up. Conservative bloggers attempt to ‘debunk’ published studies with a wide range of counter arguments ranging from honing in on small scale anomalies, personal or broad-based ad-hominim attacks against climate scientists or climate activists and the general use of misinformation to bombard opponents with assertions of facts to simply wear them down and silence them. These argumentation tactics could commonly be described as ‘trolling’ and can quite effective at convincing observers that their arguments are better. Put simply, these tactics work very well.
Trolls vs. Wizards
The important issue here is that the debate being carried out on social media, on the news and in the public eye generally is not based on scientific norms for understanding how phenomena work. Scientific discussions are typically based on abductive reasoning: argument from evidence to the best available explanation. In the blood sport where teams of trolls strive to defeat their opponents by any means necessary, the meagre weapons of abductive reasoning can do little to withstand the assault of scorn, derision, and bullshit (a word that we use here based on a precise technical defintion).
But, knowledge is power. Science is, after all, very much like magic. Science is the basis for technology, and try as they might, trolls cannot accomplish anything remotely as powerful. They can sway public opinion, but they cannot cure disease or prevent natural disasters. They cannot send ships into space or understand the mysteries of fluid dynamics in the upper stratosphere.
We must enable the explanatory power of scientific knowledge to address these counter-arguments as explicitly and powerfully as possible. At present, the scientific community does not possess the necessary power to challenge the trolls. This is was best said by Ben Goldacre in the last chapter of his book ‘Bad Science: Quacks, Hacks, and Big Pharma Flacks’. He writes:
“To anyone who feels their ideas have been challenged by this book or who has been made angry by it - to the people who feature in it, I suppose - I would say this: you win. You really do. I would hope that there might be room for you to reconsider, to change your stancein the light of what might be new information (as I will happily do, if there is ever an opportunity to update this book). But you will not need to because, as we both know, you collectively have almost full spectrum dominance. Your ideas - bogus though they may be - have immense superficial plausibility, they can be expressed rapidly, they are endlessly repeated, and they are believed by enough people for you to make very comfortable livings and to have enormous cultural influence. You win.”
Personally, I am not comfortable with this easy capitulation. I prefer to take a leaf out of Gandalf’s playbook even when faced with a daunting powerful foe.
Countering the troll ‘full spectrum dominance’ will require the development of transformative approaches to remove barriers that laypeople experience in understanding complex scientific concepts. We will need to make the work more inclusive and more democratic. We may need to transform the way scientists work and the way science is taught. This will require impeccability, creativity, honesty, and courage.
Information Science Wizardry
So, here are some observations and strategies to consider going forward.
- Modern information technology is changing many aspects of scientific work, creating new opportunities
and paradigms. Amongst these methods include:
- The scalability and speed of ‘big data’ systems allows easy analysis of very large data sets
- Deep learning and modern machine-learning methods provide groundbreaking AI performance in tasks like Data mining, Natural Language Processing, Image Classification and Document Processing.
- In particular, deep reinforcement learning permits robots and automated systems to win games and learn complex behaviors
- Forecasting methods provide powerful new methods of generating predictions based on data.
- Social Media research permits us to track and understand some of the impact of misinformation in society.
- Science information infrastructure is beginning to provide systems for reproducibility, scalability and increased rigor such as Workflows, Ontologies, Information Integration systems.
- A key capabilty is tracking the provenance of knowledge: What is the evidence that supports our argument that a given claim is true?. This is an area of continuing, active research.
- Creative methods for data visualization are becoming more common and more powerful.
- Within the climate change debate, previous attempts where scientists have adopted ‘trollish’ methods
- When researchers in England attempted to convert their scientific perspective into a political strategy, leaks of their emails that revealed their attempts to construct a robust and compelling poitical argument involved ham-fisted attempts to silence critics and steer the conversation. ‘Climategate’ ensued, doing real and lasting harm both to the climate change debate and also to the credibility of academics as a whole.
- More recently, attempts to create an expedient, powerful, simple talking point was the often-quoted ‘climate consensus’ figure. This was the product of a 2014 paper that boldly states: “Among self-rated papers expressing a position on AGW (anthropogenic global warming), 97.2% endorsed the consensus” (ref: Cook et al 2014). Unfortunately, even a simple review of this study’s own data, reveals vulnerabilities in the study that are easily revealed, see this blog post: ‘a climate falsehood you can check yourself’. Attempting to use the dark arts of spin when creating a scientifically-driven policy argument is a bad idea.
- We cannot and should not attempt to play these people at their own game. We will lose.
- At the 2017 White House Correspondents Dinner, Hasan Minhaj said “We’re living in this strange time, when trust is more important than truth”. (video). We have to find ways to establish trustworthiness with people who currently don’t believe the research and choose instead to grasp, easy-to-understand, wrong answers.
- Currently, the most accessible repository of the world’s scientific knowledge
is the scientific literature. This provides a valuable resource for knowledge engineering work
and building models of what is reported in the literature can provide insight into the underlying
subject and influence public opinion.
- This was the general idea of the Cook et al. 2014 consensus study but they did not dig deeply enough into the science.
- What if we could take this further and use machine reading methods to extract and organize the evidence reported in the 12,000 papers they examined?
- What if we could illustrate this evidence and showcase the scientific argument in precise detail?
- Perhaps we could help tailor our view of the politics to more closely align with the scientific evidence, rather than only using the scientific evidence to bolster a preconceived underlying political position.
- There are other related efforts attempting to render aspects of public life more fact-based and
data-driven. This provides a working community of data-providers, developers and end-users as
well as possible frameworks for increasing the scope and impact of technology in multiple areas.
- The FORCE11 group (‘Future Of Research Communication and E-Scholarship) is a wide-ranging academic / industry community with a broad mandate to bring about the transformation of scientific communication.
- ‘Solutions Journalism’ provides a powerful appraoch to communicating uncomfortable issues to the public. By surveying how problems are being solved and then framing discussions of difficult subjects, propopents of this approach have shown that members of the public are more engaged and receptive to reporting when framed in this way. Such an approach could work well for how we communicate the application of scientific methods to policy.
- Steve Ballmer, the ex-CEO of Microsoft, has financed and driven ‘USA Facts’, a website that examines the financial ‘score card’ of the United States as if it were a business. A recent Freakonomics podcast (‘Hoopers! Hoopers! Hoopers!’) showcased this interesting project and dealt briefly with the subject of outcomes and how one might measure them. This is the purview of the social sciences and likely requires some expertise from within the field of education theory or psychology to really
- A number of non-profits have similar missions: ‘Data 4 America’ is one such organization.
- The public are very receptive to scientific content when it is presented in a compelling and interesting way.
- Organizations such as the Technology Entertainment Design conference (http://www.ted.com/) are massively popular and provide an excellent template for packaging and presenting complex and compelling scientific ideas.
- Blogs such as framework Radiolab, Science Friday and Freakanomics regularly describe new scientific developments in a public forum with great results.
- MOOCs (such as Coursera) and online courses provide a wide range of course material to teach complex subjects. ‘Science Driven Public Policy’ could be a subject that we could develop and teach.
- Citizen science projects (such as Galaxy Zoo and FoldIt) permit members of the public to directly contribute to the scientific endeavor. This is interesting, fun, educational and could be a vehicle for engagement for science-driven policy.
- Academics typically present their ideas as powerpoint slides, but animation and storytelling methods could better illustrate their work to the public. An excellent example of this technique is this video by Pindex describing the Dunning Kruger effect (and narrated by Stephen Fry).
- It is important to note that metaphor and analogy are crucial tools that help translate complex scientific ideas into commonsense language. Finding the right framework for this messaging is an important aspect of this communication.
- We must recognize that this is an adversarial situation where our opponents will use literally
every rhetorical trick to counter a scientifically-defined viewpoint. We must counter the trolls directly
by understanding, unpacking and attacking their arguments. We should do so explicitly, ruthlessly and with as much
transparency and authority as possible.
- A terrific example of how the trolls work is the PragerU, right wing ‘educational’ website. Consider this anti-climate change video which attempts to debunk the Cook et al 2014 consensus paper. Some of the arguments are nonsensical (including an absurd apparent attempt to appeal to an antivaccination argument), but some carry a little more weight. The production of the video and carries the listener through the logic of the argument well, making emphatic statements that boldy bullshit the listener to serve their underlying argument. To counter this, we should analyze, deconstruct and refute their argument, perhaps in the same format but with a great deal of underlying support from data and established existing research.
- The work of Walton et al. 2013 on Argumentation Schemes provide a fascinating theoretical framework for formalizing how arguments are put together. This is an approach widely used in developing AI-support tools for legal argumentation, but could well be applied here.
- Finally, Computational Social Network Sciences is a powerful emerging field of AI research, that can provide insight in the emerging online world of politics. Colleages such Emilio Ferrara and Kristina Lerman study how people interact with policy through social media, social bots and each other. Understanding the dynamics of these interactions could be crucially valuable in developing effective technological strategies.
What can we do?
Our goal would be to enable the use of innovative, cutting edge, AI research within the context of policy development. Our strategy for doing this would be by developing methods to leverage and utilize scientific expertise and knowledge in politcally-relevant situations. If we could also better understand the rhetorical positions of identifiably-anti-scientific positions within public discourse. If we understand our adversaries, then we can defeat them more easily.
An initial pilot effort could be to re-examine the scientific literature described in the Cook et al. 2014 consensus study by developing detailed semantic models of the data being cited in those papers. Our job is to explore and explain the science to the public: exploring, explaining and educating through accurate reporting of the abudictive reasoning used to understand what is going on. We may explicitly contrast our approach to that of non-scientific arguments being made but always from the point of view of educating people to think scientifically, and never engaging in a polemic, fruitless discussion. If a climate-skeptic cites counterevidence, we will attempt to understand it rationally and scientifically. After all, as scientists we want people to poke holes in our models and find their flaws. Here, we would welcome such things with politeness and appreciation.
Multiple challenges threaten this plan:
Scientific work is complex, difficult to understand and challenging to execute. In order to be able to execute their work well at all, scientists perform technical feats that are difficult to record accurately, let alone reproduce. Work in the field of semantic E-Science (including ontological modeling and workflow development) make it possible to reproduce even very complex data analytics, given the additional time and effort required to model them.
There is a lot of knowledge to work through. curating information from the literature is a slow and laborious process (especially since scientific arguments do not tolerate errors well). Developing methods of automation of the curation task may speed up how representations can be populated. Needless to say, this is an area of active research and might form the basis of a focused study on the climate change literature.
Communicating complex scientific ideas is difficult. The popular science media community provides a vehicle to do this through magazines, podcasts, books, television and other media. Relying on these traditional methods can only go so far. Data visualization methods can provide a far more compelling and exhaustive view of a complex subject. This astonishing representation of the casulties of WWII is an example of a series of data visualizations that tell a compelling story in a linear fashion. We may need to examine new, non-linear methods to explain and explore the complexities of the subject of climate change.
Engaging people in this endeavor requires us to go beyond simple research. For this work to have an impact, we will require outreach and involvement far beyond the simple development of novel technology.
This post really has three purposes. Firstly, to frame the challenge as a conflict against a well-funded and powerful adversary. Secondly, to pitch the idea of developing scientific knowledge technology to ‘wizardly’ advocacy groups. Finally, to propose an initial pilot study. This vision document seeks only to present a picture of how to do this in broad strokes in a single, simple domain: clarifying and solidifying the climate change debate. From these humble beginnings, we we would ultimately seek to provide better access to research for policy makers wanting to incorporate existing research from any given field into their platform.