S3T August 11 - Learning Curves and Accountability, Crypto as GOP wedge issue, testing Supermind Ideator, OverflowAI...

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In this edition:

• Change Leadership Skills: The constant emergence of new technologies presents a specific set of dilemmas for technology-related governance teams and regulators.
• Macroeconomics: Corporate opportunism creates the kind of inflation that interest rates don't address. Crypto as a wedge issue for GOP.
• Emerging Tech: Stack Overflow rolls out an experiment in AI-based semantic search. Plus: test drive of MIT Supermind Ideator.

📖️ Change Leadership Notebook: Learning Curves and Accountability

Who is responsible for Security by Design?

This longer Techcrunch piece on the Cybersecurity and Infrastructure Security Agency (CISA) highlights a practical set of challenges that change leaders should understand so they can be ready to partner with governance and regulators to innovate in a responsible and timely manner.

The Techcrunch piece explains the implementation challenges for the next generation of security by design and offers a path forward. On a tactical level, it's highly recommended reading for CISOs and security professionals.

It also provides a perfect springboard for thinking in a more strategic manner about the way that innovators and governance or regulator teams need to collaborate without compromising each other's integrity and mission.

The Challenge of Accountability in an Age of Accelerating Innovation

Governance teams and regulators alike have a similar set of tasks:

• identifying risks,
• establishing best practices,
• enforcing compliance, holding the right parties accountable

The constant emergence of new technologies presents a specific set of dilemmas for technology-related governance teams and regulators:

• How do you remain expert enough to provide meaningful scrutiny and guidance?
• How do you avoid slowing down the pace of innovation, simply because you're not learning as fast as you need to?

Case in point: who's accountable for the actions of autonomous agents?  

As the diversifying capabilities of AI increase the number of autonomous agents taking actions with real-world impacts, a new kind of risk management and economic math will need to evolve and be able to answer these 3 questions.

• Who owns and operates these autonomous agents?
• Who is accountable for what these agents do? And the impact they have?
• Who has the right to extract profit from the economic activity that these agents provide?

In the current status quo, a similar set of 3 questions exist, though they have so far only been applied to non-autonomous agents:

• Who owns and operates a platform or corporation
• What control are they expected to maintain (and be able to prove in an audit)
• Who has the right to extract profits from the operation of these assets?

Corporations and their sometimes cozy collaborators at the federal level, have been clever at separating these 3 questions in ways that optimize gains while minimizing taxes and accountability for corporations - often at the expense of everyone else. Creative accounting, corporate structures and legislative loopholing have been raised to an art form in service of maximum gain for minimum responsibility.

To date, the safety net underneath all this high-flying fun has been a specific segment of the tax base - the least empowered, least informed, least likely to be able to take advantage of tax shelters - you guessed it, the lower to middle-income taxpayers who always get stuck with the bill. Bailouts, cleanups, recoveries, you name it, just get added to the tab of the lower to middle-income taxpayers.  

From Wall Street and Capitol Hill this has always looked like the safest most comfortable approach (whatever the objections from Main Street). But in a highly automated future, this brand of opportunism could impose new and unprecedented kinds of risks and impacts that lower to middle taxpayers will lack the resources to underwrite.  

In other words, the status quo  - which to be clear isn't working in an equitable manner now - definitely will not work in the AI-driven future. How will we learn together and prove out what will work to ensure good outcomes?

Getting up the Learning Curve Together

Innovation-minded change leaders can foster a collaborative and constructive relationship with regulators and governance boards while maintaining their integrity and commitment to change. Here is a simple playbook of key strategies to leverage when working with governance boards (at the corporate or industry level) or government regulators :

• Proactive engagement: Instead of waiting for regulators to intervene, change leaders should proactively engage with them early on. Admittedly some regulators have not made this easy. Seeking input and feedback during the development of new technologies or initiatives can help identify potential regulatory concerns and address them collaboratively.
• Transparency and open communication: Change leaders should maintain open lines of communication with regulators and governance boards. Being transparent about the intention of a specific innovation as well as its potential risks will drive better understanding and trust-building than withholding or parceling out information piecemeal. Openly discussing the benefits and challenges of an initiative shows a commitment to responsible innovation.
• Balance long-term and near-term: Share the long-term vision for positive change and the benefits innovation can bring to society and industry, as well as the near-term plans for advancing that long-term vision. Demonstrating a commitment to the greater good and sustainable progress can resonate with regulators and governance boards who also have the responsibility to maintain appropriate controls and safeguard the public interest.
• Demonstrate compliance and responsible practices: Change leaders should exemplify a concern for ethics, and a strong culture of compliance and responsible practices within their firms. Adhering to industry standards, best practices and ethical guidelines should foster a better working relationship.
• Educate and orient about emerging tech and the changes they cause: Change leaders can play a role in educating regulators and governance boards about the potential benefits and risks associated with new technologies. Offer clear but thorough points, backed by data and research, in the spirit of helping governance teams or regulators understand the important context and make more informed decisions. If possible bring neutral 3rd parties (who have nothing to gain) to the table who can provide explanations and education about the emerging capabilities and risks.
• Positive engagement during regulation processes: When new regulations are being considered, change leaders can actively participate in the consultation process. By offering insights, data, and constructive feedback, they can help shape regulations that are both effective in ensuring accountability and supportive of innovation.

Don't let yourself or your team fall into an all-or-nothing false tradeoff mindset where you assume that you either have to slow roll innovations to please regulators or do an end run around regulators to make the innovation go forward. Building collaborative relationships based on trust and shared objectives can lead to more effective governance without compromising innovation or accountability. By following these approaches, change leaders who are driving new innovations can do their part to ensure a productive working relationship with regulators and governance boards while staying true to their mission as committed leaders of change and ensuring the integrity of the regulatory and accountability processes.

Macroeconomics: the best of times and the worst

The kind of inflation that interest rates can't impact

Annie Lowrey delivers a great summary of today's mixed economic picture. By historic standards, many economic indicators suggest we are better off than ever if you compare today's numbers against historic numbers. But that misses two points:

• Inflation is causing those numbers to be higher
• The benefits are not being felt evenly  

This calls to mind Lowrey's 2020 piece on the Affordability Crisis that exposed how families were being squeezed by opportunistic "landlords, hospital administrators, university bursars, and child-care centers." This is a source of inflation that interest rates don't address.  

This aligns with findings highlighted by Josh Bivens (Economic Policy Institute) that corporate profits have contributed disproportionately to inflation. Key points of the argument summarized here:

• The Nonfinancial Corporate sector of the economy covers goods and services, and comprise ~75% of the private commercial sector.
• This large sector of the economy has very strong clear data about its costs and margins
• Since mid-2020 this data shows 6.1% annual increase in overall costs - sharply up from the previous annual average of 1.8%
• 53.9% of cost increases is attributable to profit margins while only 8% is attributable to increased labor costs.
• In the previous 40 years (back to 1979) profits contributed 11% and labor costs 60%

See chart below for visual comparison.

Rethinking how we measure inflation

In summary, I think it's vital for leaders to be clear on exactly why headline inflation indicators paint a picture of moderating inflation, even as other more insidious forms of inflation persist and continue to rise.    

The Federal Reserve's war on headline inflation - an arbitrarily narrow set of indicators that don't fully reflect the impact of inflation on families - amounts to fairly useless pageantry, if the root causes of inflation are not addressed and the financial outlook for US families remains as bleak as ever.  

It may be appropriate for Congress to ask the Federal Reserve, central banks and other economically impactful agencies to rethink how we measure inflation. Definitely a topic to take up with your elected representatives.

Summing up the crypto heyday

Easy Money a new book by actor Ben McKenzie (of O.C. and Gotham) is highly critical of the crypto industry, riffing off the scandalous headlines of the last two years, with some fascinating insider takes.

As Vox points out this is yet another celebrity talking about crypto (a genre with mixed results), but I do think the book and its message is worth looking at for three reasons:

• This book summarizes the fears and accusations of the anti-crypto lobby which includes Elizabeth Warren, Gary Gensler, and notable others, and I expect it to become something of a respected cultural reference for these groups. The book scored an endorsement from no less than Ron Chernow, noted author of the critically acclaimed books Hamilton, Grant, and others (see “Praise” section at the publisher’s product page).
• The book provides insight into a possible wedge issue for GOP: The book and its author were featured on the July 23 podcast of the Bulwark, a respected standard-bearer of the never-Trump wing of the Republican party. This stands in sharp contrast to numerous other GOP members who have come out in favor of crypto.
• The book is also a useful index of what crypto haters refuse to see: While McKenzie and co-author Jacob Silverman are right to call out the scams, the book does not appear to recognize the new powerful financial building blocks offered by blockchain and token architectures, and what can be -  is being - built with those new financial building blocks.

I do think that books (or other materials) that carry themes like this have usefulness for thoughtful regulators as well as crypto industry leaders who are developing governance frameworks and want to build trust.

Emerging Tech

OverflowAI: GenAI comes to Stack Overflow

Stack Overflow is rolling out a new AI-based semantic search it calls OverflowAI. In this, Stack Overflow is attempting to walk a line between maintaining the trust of the community, with its strong emphasis on human expertise, and the desire to leverage the power of GenAI. Sign up for updates and learn more at the new Stack Overflow Labs page here.

Testing MIT's SuperMind Ideator

I was one of the first selected to try out MIT’s Supermind Ideator, an AI powered assistant designed to boost the creativity and brainstorming of teams and individuals.

Key Takeaways:

• Provides a structured approach to exploring a problem and potential starting points for solutions.
• Does not yet have strong ability to reference sources. In one attempt to provide a source, the URL to the source could not be retrieved.
• Demonstrated the ability to connect to other data sources (in this case the Supermind Design Library...a database of innovation ideas).
• Try it in informal and non-confidential brainstorming exercises.

Hi, I’m Ralph Perrine, founder of S3T Newsletter. Thanks for reading this week’s edition!

I created S3T to empower change leaders with the knowledge and insights they need to navigate the ever-evolving landscapes of economics and emerging tech.

Your feedback is greatly appreciated and matters to me, always love to hear what you are working on and how S3T can bring more value to your learning and success.

Direct message me @ralphperrine on LinkedIn or Twitter anytime.

Cheers,
Ralph Perrine

Opinions expressed are those of the individuals and do not reflect the official positions of companies or organizations those individuals may be affiliated with. Not financial advice. Authors or guests may hold assets discussed.