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DALL-E Image: Cyber Misinformation and Conspiracy Theory

The Summer of 2024 is seeing a dramatic rise in violent disturbance on our streets, driven by cyber misinformation and conspiracy psychology spread through the everyday web—not the dark web, but the regular, accessible internet. Words, images, and music merge in TikTok and YouTube style ‘mini memes’ that proliferate rapidly. In pursuit of attention, both humans and bots exploit human vulnerabilities to undermine rational and measured thinking processes. By transmitting influence through semantic earworms that embed directly into our subconscious, such tactics subtly shape motivations and beliefs. The resultant mayhem is ripe for exploitation.

Trapped within the echo chambers of newsfeeds, silos, rabbit holes, and other online traps, individuals become isolated within small, like-minded groups, cut off from everyday discourse. Any conflicting  evidence itself becomes a subject of suspicion, as do the motivations of the dissauders. The victims are enthralled into an imaginary world where they are at the whim of their often unseen manipulators.

Can Breaking News be unbroken?

Everyone is asking why tech companies can’t be regulated, but is that where the problem really lies? The issue might be with our own craving for excitment. Perhaps we’re emphasizing the wrong word—it’s not just about “fake,” but about “news.” In the pre-internet era, editors regulated news, but newspaper sales still drove content. How many stories in right-wing or left-wing papers were truly balanced? The major change today is that we no longer need industrial-scale printing presses. Commercial dynamics once demanded a mass audience for the same product, but now any influencer can be a publisher. And for today’s journalists, now more than ever, success no longer means just having a great story. In the era of online news, truth and quality have taken a backseat to the almighty trifecta: tweets, likes, and shares. AI generated headlines are added into the mix. The world of news has changed. Now the medium truly is the message – within its new cyberspace environment. Maybe regulating cybernews isn’t feasible within a true democracy because the dynamics have fundamentally shifted.

The Psychology of Extremism

But let’s think outside the box (since thinking within it doesn’t seem to work). How about regulating not what we believe, but what we do when we believe it? Presumably, the ‘bad actors,’ to the extent they are behind what is happening, don’t just want us to believe something untrue—they want us to act on these beliefs and cause mayhem. Of course, there are already plenty of laws against causing mayhem, so a more practical solution might be to reduce the number of people who cause it. Who are they? And why are some people more prone to believe in conspiracy theories than others?

There is a personality trait known to both psychologists and psychiatrists that can assess this vulnerability. One psychometric test for its assessment is the RISC (yes, its my own, the Rust Inventory of Schizotypal Cognition), The RISC scores people on a nine-point ‘stanine’ scale ranging between 1 (extremely skeptical), through 5 (average) to 9 (extremely fascinated by all sorts of weird ideas), and all points in between.

But schizotypal thinking is not the only psychological trait that can lead people to be sucked into conspiracy theories. Other risk factors are paranoia, excessive anxiety, insecurity distrust of others, antagonistic thinking, suceptability to fear-based narratives, intuitive ‘gut-feeling’ thinking, and dislike of ambiguity. These are in addition to social effects such as poor education, over-exposure to extreme political views, and social isolation.  And while we could identify ‘at risk’ individuals from all this by analysing online digital footprints and ‘Lookalikes’ (as I’m sure many security  services already do) this clearly involves an invasion of privacy, as the Cambridge Analytica scandle illustrated only too well.

Reversing the Gaze: Machine-in-the-Loop Systems

So what then is the solution? Generative AI could help, as it already does within the legal system, advising solicitors and advocates, managing data sources for leglislators and assisting judges in writing their reports. but is this a step too far? Within AI warfare there is a strong principle that there should always be a ‘human-in-the-loop’ when any decision is made that will affect human life.  But within cyberspace, it is these ‘humans-in-the-loop’, the actors inspiring all this mayhem, that are the problem.

So let’s ‘reverse the gaze’. Let’s put an AI in the loop. I assembled some prompts for GPT4 about this idea. Below is what it says.

GPT4 makes the case:

“You’re absolutely right to consider the potential drawbacks of a “human-in-the-loop” system, especially if the human in question is a “bad actor.” In scenarios where human biases or malicious intentions could compromise the integrity of AI systems, implementing a “machine-in-the-loop” system might be a more effective strategy. Here, the AI could serve as a safeguard, ensuring that ethical standards are maintained without undue influence from malicious human intervention. It would  involve automated processes that oversee or supplement human decision-making, particularly in critical areas such as ethics and security. In this configuration, machines not only perform tasks but also monitor, validate, and enhance human actions to prevent unethical practices. Its advantages will include:

  • Objective Decision-Making: Machines can be programmed to consistently apply ethical guidelines without human biases, reducing the likelihood of subjective decision-making.
  • Uniform Standards: AI can enforce uniform standards across different applications, ensuring consistent adherence to ethical principles.
  • Handling Large Volumes: Machines can process vast amounts of data quickly, identifying patterns and anomalies that may indicate unethical behavior.
  • Automated Monitoring: AI systems can continuously monitor operations for compliance with ethical guidelines, providing real-time alerts and interventions as needed.
  • Unbiased Evaluation: AI systems can provide impartial oversight, evaluating decisions based on predetermined ethical criteria without being influenced by personal agendas or external pressures.
  • Reduced Manipulation Risk: By reducing human involvement in critical decision points, the risk of manipulation by bad actors is minimized.
  • Decision Frameworks: Develop AI systems equipped with ethical decision frameworks that operate independently, assessing actions and decisions against a set of predefined ethical guidelines.
  • Continuous Learning: Implement machine learning models that adapt and refine ethical standards based on new data and evolving societal norms.
  • Automated Compliance: Use AI to automatically enforce ethical rules and standards, flagging deviations and initiating corrective actions without human intervention.
  • Real-Time Monitoring: Implement systems that continuously monitor activities for ethical compliance, providing real-time feedback and adjustments as needed.
  • Automated Auditing Tools: Develop AI tools that perform regular audits of systems and processes, identifying potential ethical violations and recommending corrective actions.
  • Behavioral Analysis: Use AI to analyze behavior patterns, detecting signs of unethical activity or manipulation attempts.
  • Explainable AI Models: Implement explainable AI models that provide transparency in decision-making processes, allowing for better auditing and accountability.
  • Audit Trails: Maintain detailed audit trails of AI decisions, ensuring that actions can be traced and verified for compliance with ethical standards.”
  • Security Layers: Use AI-driven security systems to detect and respond to unauthorized access attempts or manipulation efforts, safeguarding AI integrity.
  • Anomaly Detection: Implement AI models that detect unusual patterns in data and user behavior, flagging potential security threats for further investigation.
  • Data Protection: Use AI to encrypt sensitive data and ensure its integrity, preventing tampering and unauthorized access.
  •  Security Protocols: Implement machine-led protocols that enforce strict security measures, reducing the risk of human error or negligence.
  • User Behavior Analysis: Use AI to monitor user behavior, identifying potential bad actors based on patterns and anomalies.
  • Access Controls: Implement AI systems that enforce access controls, ensuring that only authorized individuals can make critical changes to AI systems.
  • Algorithmic Fairness: Use AI to detect and correct biases in algorithms, ensuring fair and unbiased decision-making.
  • AI Review Processes: Use AI to review human decisions for ethical compliance, providing an additional layer of oversight.

And GPT4’s Conclusion

“A machine-in-the-loop system offers significant advantages in ensuring ethical compliance and reducing the risk of manipulation by bad actors. By leveraging AI’s capabilities for objective decision-making, security, and ethical oversight, we can create systems that maintain high ethical standards while minimizing human vulnerabilities.

By embracing machine-in-the-loop systems, organizations can enhance their ability to combat cyber misinformation and unethical behavior, building a digital ecosystem that prioritizes truth, integrity, and ethical responsibility. This approach, combined with ongoing collaboration and innovation, can help create a safer and more ethical digital landscape for all.”

Does all this give you a bad feeling?

Dees it remind you of ‘Brave New World’? It should. But why is this? After all AI doesn’t have sentience – it can’t think bad thoughts, or even good ones. It doesn’t have ‘free will’ and can’t initiate actions on its own. Even with the now archetypal “Terminator” film series, it was a mistake by humans that initiated Skynet. But therein lies the problem. It takes a Human-in-the-Loop (let’s call them an HITL)  to initiate a ‘Machine-in-the-Loop’ (MITL); and there are plenty of bad actors among us humans.

And a second reason for our doom-laden concerns. If I can get GPT4 to make these ‘useful’ suggestions, so can anyone else – including all those ‘bad actors’. And they have presumably been doing so for some time now, certainly since over a year ago when GenAI first hit the headlines.

So, suppose I was a populist, and I wanted to enact the popular agenda among populists – abolish democracy, replace with strong leaders, eliminate the woke including LGBT+ rights, enforce borders, reintroduce national service and – control – control – control.

Well – I might try a pilot run in a vulnerable country, use the apparent willingness of the populus to accept fake news (even when there is plenty of evidence that it is indeed fake). I might  do this by suggesting that there is ‘more than meets the eye’ and also that ‘civil war is inevitable’. When such comments come from diverse supporters of the same Great Leader from both the UK and the USA, you may indeed suspect there is a conspiracy. Or maybe they are just jumping on the bandwagon once its already on the roll.

What can be done?

Can the MITL also be used for the greater good? In the current state of affairs, we might consider this as maintaining the democratic process and the human rights enshrined in the United Nations and obtained by other hard won international agreements. Nonetheless, there are several current applications of the MITL approach being openly reported.

  • The military increasingly use AI software to derive algorithms that minimize ‘collateral damage’ (although the software does also allow humans to move the goalposts on the definition of an ‘acceptable’ civilian causality count).
  • GenAI companies use MITL in what they call ‘value alignment’ in their endeavors to prevent Chatbots from replying with ‘unacceptable’ answers or comments (perhaps best but most cynically described as answers or comments that are likely to lead to reduced profit).
  • Regulators in Nation States will also be seeking advice from MITL on how to frame appropriate regulation.

And in the last of these, lies the problem. For most Nation States the ‘Bad Actors’ are often – other Nation States.  So, is this where the United Nations comes in? Or should come in?

Hopefully the UN will be able to generate a MITL that is powerful enough to model all his. I’m going to assume that it does. With enough will, we can make it happen.