Potential risks of Augmented Learning Collaboration (ALC) and their mitigation

As any new technology, ALC carries not only the potential of great progress but also substantial risks. Which are those risks and how can they addressed?

Clearly, whilst the examples of societal transformations provided in the different FAQs on this website illustrate how far the impact of ALC can go, we only have touched upon a few high-profile cases. Imagine how public security could evolve with extended identity, leading to a safer and a freer world at the same time, as it would be possible to control important aspects such as trustworthiness of people, without revealing their identity. Imagine how we could enable new more agile forms of international cooperation on crime, by getting symBots in charge of managing criminal case files as trusted third parties, and strictly ensuring that only authorised officials could access the information. Imagine how we could enrich complex supply chains, by giving products their own symBots, encapsulating IOTs, interacting with tax symBots, carbon credit symBots, custom symBots etc. Imagine how consulting, legal and other professional services could change, by combining legal LLM-encapsulating symBots with human expertise, and embedding micro-transactions, enlarging the access of Mrs. and Mr. Everybody to high-quality legal advice. Imagine how public, social, and business services could evolve by empowering and guiding users, and only involving the right “service representatives”, when users cannot help themselves, and systematically using this experience to improve the systems. Et cetera. Et cetera.

Clearly, we are only starting to imagine the beginning of what is possible.

However, we should not fool ourselves. As with any high-potential technology it can be used for the best and the worst! Understanding the risks is essential but unavoidably partial and incomplete. As we have seen above, it is difficult to imagine all the potential applications of ALC, especially when combined with other technologies such as AI, blockchains and / or IOT. It is as (probably as) difficult (if not more) to imagine what might go wrong.

When the author asked ChatGPT, it came up with the following: While ALC (Adaptive Learning and Collaboration) holds the potential for significant benefits and transformative change, it is essential to consider potential systemic risks that may arise from its development. Here are some examples of systemic risks associated with the implementation of ALC:

  • Data Security and Privacy: As ALC relies on the exchange and processing of large amounts of data, there is a risk of data breaches, unauthorized access, and privacy violations. Safeguarding sensitive information and ensuring robust data protection measures are critical to mitigating these risks.
  • Technological Dependence: ALC heavily relies on technology infrastructure, including servers, networks, and software systems. Any disruptions, such as power outages, cyberattacks, or software failures, could lead to significant disruptions in ALC operations, affecting collaboration and learning processes.
  • Algorithmic Bias and Discrimination: ALC systems utilize algorithms to make decisions and provide recommendations. If these algorithms are biased or discriminatory, it can perpetuate existing societal inequalities and reinforce unfair biases, leading to negative consequences for marginalized groups.
  • Inequality and Access Disparities: ALC implementation requires access to reliable internet connectivity, technological devices, and digital literacy skills. Unequal access to these resources can exacerbate existing social and economic inequalities, creating a digital divide and excluding certain individuals or communities from benefiting fully from ALC.
  • Ethical Considerations: ALC raises ethical questions regarding user consent, transparency, accountability, and the potential for unintended consequences. It is crucial to address ethical concerns related to data collection, algorithmic decision-making, and the responsible use of technology in ALC to prevent harm and ensure ethical guidelines are in place.
  • Loss of Human Connection: While ALC enables virtual collaboration and learning, it may also lead to a reduction in face-to-face interactions and human connection. It is essential to strike a balance between leveraging technology for efficient collaboration while maintaining meaningful human relationships and social interactions.
  • Economic Disruption: The widespread adoption of ALC can lead to job displacement and changes in labor markets. Certain roles or industries may become obsolete, requiring workforce adaptation and reskilling to ensure smooth transitions and minimize economic disruptions.
  • Cognitive Overreliance: ALC systems provide valuable support and recommendations, but there is a risk of individuals becoming overly reliant on these systems, potentially diminishing critical thinking skills and edecision-making abilities.

Addressing these systemic risks requires careful planning, proactive risk management strategies, ethical guidelines, and ongoing evaluation to ensure the responsible and inclusive development and deployment of ALC technologies.

Not bad for a start. In fact, the risks identified by ChatGPT are all more or less addressed by the logic of ALC.

  • Basing the ALC technology on a decentralised Web 4.0 architecture (as SymPlace with ONE) enables privacy-by-design.
  • Starting from the collaboration between collaborating humans, and “pushing” them with symBots to actively participate, instead of replacing human cognitive effort and inter-human collaboration with algorithms
  • Reducing cognitive overload by getting VPAs to adapt to the specifics of users, e.g., their profile, their workload, their priorities…
  • Employing systematically MetaSymFlos to control, evaluate and govern symFlo templates / symBots and symCommunities, thus identifying biases and countering them by adapting the structure of groups, configuring anonymity, “play” with timing and pacing, including dedicated symBots, etc.
  • Ensuring easy access for the economically and socially most disfavoured, even empowering them, at least for SymPlace, with an adapted economic model that will reduce inequalities rather than reinforcing them.
  • And, last but certainly not least, strengthening human connections – the idea is not to spend less time, ut to spend more quality time together, not only because we are more efficient and effective, but because not all human interactions are equally valuable. Organising a lunch with a friend and meeting people to have a deep meaningful discussion (or an enjoyable highly funny moment, no value judgements) are not the same. Checking out if your doctor is available, or answering a bunch of diagnostic questions, and then getting him to use her.his brain under high pressure to make sense of our complex perhaps contradictory data, is not as valuable as getting him.her to have a warm meaningful discussion. Lecturing to a large audience or running an exam, is a less valuable usage of a teacher’s precious time than to spend some time to freely interact with students to help them discover the beauty of a domain they do not yet fully grasp. The point of ALC is to free people of the former so that they have time for the latter.

However, this analysis (and response) is clearly insufficient. Most negative collateral impacts of new technologies have come from “unknown unknowns”, i.e., from risks that only emerged as the new technology (industrial, digital, social…) became sufficiently impactful and widespread. Some of these risks will require difficult trade-offs and decisions to make, which may significantly and lastingly affect Society. This is one of the reasons, we think that SymPlace, should ultimately be owned by nobody and be governed by everybody who uses it. This governance will not be disconnected from the technology but be fully part of it. As new problems appear, members of the SymPlace symCommunity will be able to initiate corresponding “alert” symFlos to explore their severity, imagine responses, come up with ways of developing and testing them, deploying them, and monitoring and evaluating them. And then being able to run, much more easily than before, experiments, to try out new approaches, to adapt to unforeseen circumstances and challenges, to explore the potential of new opportunities which tend to be the other side of the risk-coin.