Preparing for Global Dialogue: Some Thoughts from Fellow Michael Wright

The application of ethics to AI poses many novel challenges.  For example, how should we approach the bias inherent in AI systems?  How do we ensure that AI is used in a way that respects human dignity and rights?  What responsibilities do AI developers have in ensuring that their creations and economic engines are used ethically?  These are questions that traditional ethical norms might not have ready-made answers for and for which no incentives exist in the current business models wherein engineers are amorally engaged in extracting five more seconds of your time that they will then capture on their employer’s site.  Which seems harmless until you multiply you, the captive, by 2 billion.  That is 10 billion seconds of exposure to advertising or 320 years’ worth if directed at one person.

Any ethical framework will always be a work in progress.  It will need to be continuously updated and refined as our understanding of AI and its impacts on society evolve.  This is a daunting task, but it is one somebody with respect and authority must undertake if we are to harness the power of AI responsibly. However, currently, there is no entity or network of networks with universal respect or authority.  That means it is unlikely, given the rapid acceleration of technology adoption, that the world can develop an ethical construct in a useful period of time.  Unless there is a compelling reason….i.e., incentive in the new religion of finance.

The idea of incentivizing ethical behavior within financial institutions is an interesting one and there are mechanisms that could be used to accomplish this.  These could include regulatory measures, tax incentives and the use of ESG (environmental, social and governance) criteria in evaluating investments.

Regulatory measures could require financial institutions to consider long-term societal impacts in their decision-making processes.  This could mean implementing stricter laws around issues like lending practices, investment criteria and corporate governance, with penalties for non-compliance.

Tax incentives could be used to reward financial institutions that make decisions based on sustainable, socially responsible principles.  For instance, a bank might receive a tax break for investing in renewable energy, affordable housing or other projects that contribute to societal well-being.

ESG criteria are already used by many investors to assess the sustainability and ethical impact of an investment in a company or business.  But it is nearly always a look in the rearview mirror. Banks, lending institutions and capital markets could be encouraged (or required) to use ESG criteria in their decision-making processes, rewarding companies that operate sustainably and ethically.  In my experience with cost modeling for the semiconductor and solar industries (among others), when one expands the time horizon, environmental, social and governance costs become more anchored in reality and are often counter intuitive.  In nearly all cases, a ‘green’ strategy wins out over ‘status quo’ or ‘cheap, but dirty’ when looked at across generational time versus the next quarter or year.

There are many challenges to this approach.  One is the difficulty of defining and measuring “ethical” behavior.  What one person or culture considers ethical, another may not.  This is particularly relevant when considering global financial markets, which involve actors from many different cultures and ethical traditions.  Traditions which play extremely important roles, as Steve Young pointed out in his book on Kissinger’s Betrayal…thank you!

Another challenge is enforcement.  Given the complexity and global nature of modern financial markets, enforcing ethical standards can be difficult without monetary incentive.  It requires cooperation between governments, regulatory bodies and financial institutions worldwide.  With the emerging battle over reserve currencies, especially when digitized, this type of cooperation seems less plausible every day.

Lastly, there’s the issue of short-term versus long-term incentives.  Many financial institutions are driven by short-term profits, while ethical considerations, as we are learning too late, must involve long-term impacts that can only be imagined, but which must be agreed upon or we all lose.  Aligning these incentives requires a significant shift in the way that financial institutions operate.  So, I ask …what events must occur to motivate them?  More natural catastrophes at larger scale?  Nation state economic failures at scale?  Insurance companies are abandoning entire regions as this is written.

Despite these challenges, the idea of incentivizing ethical behavior in the financial industry is, I think, a compelling one.  It aligns with broader societal trends towards greater corporate responsibility and sustainable business practices and could potentially lead to significant societal benefits.  However, it would require careful thought, planning and cooperation between various stakeholders to implement effectively.  I’m becoming less and less convinced we can get the stakeholders in a room without an overwhelming existential threat and that may not occur in a timely or forgiving fashion.

Part 2

For instance, the concept of “seven generation sustainability,” which is derived from the Great Law of the Iroquois, asserts that decisions should be made with consideration of their effects seven generations into the future.  With today’s computing power, we should be able to look beyond 7 and think in terms of centuries, which not many people will or can do.

Applying this type of framework to technological adoption could help to anticipate and mitigate potential negative effects, promote longer term horizon practices and guide the development and deployment of technologies in a way that is beneficial (or the least harmful) for both current and future generations.

While I’ve always believed the concept is ethically appealing and indeed necessary, its practical implementation presents several challenges.  Just a few:

1. Predictability: It’s often difficult to accurately predict the long-term impacts of new technologies.  Consider, for example, the advent of the internet or smartphones.  These technologies have had far-reaching and unanticipated effects on society, both positive and negative.  Or our ignorant (not implying stupid, but lacking the discipline to examine the consequences) adoption of plastics and fossil fuels.

2. Accountability: Holding entities accountable for the potential impacts of their decisions on future generations can be an open-ended issue.  If negative consequences do emerge, it may be difficult to trace these back to specific decisions or entities (e.g. pfas).  Moreover, unless they are modeled and reviewed carefully, these impacts may not become apparent until long after the decision-makers are gone.  E.g., fossil fuel-based energy; plastic proliferation; monocrop agriculture….

3. Measurement: How do you measure the impact of privacy concerns or job displacement due to automation on future generations?  In Steve Young’s book on Kissinger, the issue of transition time becomes central to the outcome.  It becomes even more so when technology adoption can be nearly instantaneous across the globe.

4. Balancing present and future needs: Striking a balance between short and long can be complex, but complexity, fortunately, is nothing more than architecture.

An argument for creating a mechanism to fund a novel capability in the context of developing new ethics alongside new technologies suggests there is an opportunity for a new approach that features the specifics of time-enriched data and the constructal law of physics to create a new modeling methodology capable of at least exploring, at scale, the likely path and timing of technology adoption and identifying possible outcomes and outliers.

Dr. Stuart Albert’s work on time-enriched data has shown that time can be used to enrich data in ways that can improve the accuracy and reliability of models.  Dr. Adrian Bejan’s work on the constructal law of physics has shown that systems evolve to increase their access to available energy and minimize their dissipation of energy.  By combining these two approaches, along with studies done on complex interactive systems and systems integration, it is possible to create a new modeling methodology that can improve the accuracy and reliability of models by considering the temporal evolution of systems.

Temporal evolution, in this context, refers to the changes and development in a system over time. When applied to models, this concept focuses on how the factors or variables in a model change as time progresses.

For instance, if we’re talking about the spread of diseases, the temporal evolution of an outbreak would look at how the number of cases, the rate of spread and other important factors changes day by day, month by month or year by year.  It could involve tracking how the disease spreads through a population over time, how its virulence might change, how quickly interventions can slow the spread and more.

Considering the far-reaching implications and potential benefits of an innovative modeling methodology based on time-enriched data, work done on complex interactive systems and the constructal law, it becomes clear that establishing a funding mechanism to support its development and application is not just desirable, but essential.

This methodology promises a revolution in our understanding of various systems, from climate change and disease spread, to the evolution of technology.  By incorporating temporal evolution and principles of energy flow, this approach could improve the accuracy and reliability of our models, offering profound insights into how systems change over time.

More to the point of this discussion, the modeling methodology I have been proposing since 2019 could also play a crucial role in ethical considerations, particularly concerning the development and adoption of new technologies.  By providing more accurate models of potential future outcomes, this methodology could enable us to foresee and consider the ethical implications of our technological decisions more effectively.  This could help us uphold the ethical requirements to consider the potential impact of these decisions on future generations.

Just as the development of new technologies necessitates the evolution of ethical frameworks, the development of these advanced modeling methodologies calls for financial support and incentive structures to guide their growth.  The funding mechanism should not only support the research and development of the methodology, but also its application and integration into decision-making processes.

Such an initiative would provide economic and moral incentives for ethical behavior in our technological decisions.  It aligns with the broader societal trend towards corporate responsibility and sustainable practices.  And most importantly, it provides us with a tool to ensure that our decisions today consider and protect the interests of future generations and possibly humanity itself.

In the end, the creation of a funding mechanism to support this innovative modeling methodology is a vital step towards understanding and managing the ethical implications of our rapidly evolving technological landscape.  This is an investment not just in technology, but in the future of our society.  Do you know any takers?  People with absurd hordes of dead money and no real legacy could actually fund a project that will aid in assuring their children’s grandchildren have a better planet, a healthier population to share it with and useful and meaningful purpose as humans.

I thought it at least worth the time and effort to throw this into the mix for your consideration and give some voice to the problem with a potential solution (I used to have a rule to never let someone leave the ‘monkey’ in my office; if you come up with a problem, come in with a possible solution).

Respectfully yours,