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Happy Friday, hope you all had a great week! Here is your learning resource with the need-to-know key topics leaders are talking about this week.
In this issue
- Macro Economics - Inflation Insights. A look at this week's CPI and PPI data and its nuanced impact on different societal segments, introducing the Cantillon Effect. Plus: India's frequent Internet shutdowns are hampering its digital economy and citizens' well-being.
- Emerging Tech: Coinbase's support for Lightning and PayPal's stablecoin, and how these developments could shape future financial transactions. How will the AI Tech Sector address Regulatory Uncertainty?
- Nature Notes: Examining nature's resilience in turning former dumpsites and disaster areas into thriving ecosystems.
- For Paying Members: Designing Org & Job Family Structure
Deep dive into the future of organizational planning and talent management in the era of GenAI.
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.
Inflation - doing what Inflation does
This week's CPI and PPI figures indicate continued moderation in the rise of headline inflation, and increases in the prices that companies are able to sell wholesale goods and services for. While these are useful and optimistic macro indicators, it is important to remember that inflation's impact is not fully tracked by these figures and that both inflation and interest rates have different impacts on different segments of society.
For example, when interest rates are hiked in an attempt to control inflation, families will feel the pinch in the form of higher borrowing costs for loans or credit cards. But when interest rates fall, the benefits are disproportionately reaped by corporations and financial services a phenomenon referred to as the Cantillon Effect. This is why the stock market goes up every time there's any hint the Fed will cut rates.
The Cantillon Effect
The Cantillon effect refers to the uneven distribution of money in an economy. The phenomenon is named for Richard Cantillon who questioned whether money impacts all segments of an economy equally or whether it impacts some more favorably than others.
According to this view, when a central bank pumps more money into the economy, the benefit does not happen evenly. The Austrian economist Friedrich August von Hayek compared this monetary expansion with honey. If you pour honey into a cup, it won’t spread out evenly. It will clump in the middle of the cup first before spreading out.
To apply this to monetary expansion (either the injection of stimulus money or the lowering of interest rates), those who have first access to the money (banks, large corporations) are able to access the money first and use it for loans and investments. This can cause prices to rise before the rest of the population (the less wealthy) has seen any benefit. They pay higher prices even though they may not have benefited from the increase in money at all.
- Foundation for Economic Education: The Cantillon Effect: Because of Inflation, We’re Financing the Financiers
- Austrian Economics Center: The Cantillon Effect and Populism
India's Digital Economy hampered by Internet shutdowns
Regional Indian authorities have followed a practice of shutting down Internet access in response to protests, cheating on exams, communal violence, and other concerns, as detailed in this Human Rights Watch piece. The staggering toll on both individuals as well as the national economy is coming to light (see WSJ: India Keeps Pulling the Plug on its Digital Economy):
- $4.8B in lost economic activity
- 120 million+ people impacted - no work, no food, no services.
India leads the world in depriving its citizens of Internet access - a status that undermines its Digital India initiative. You can help by sharing this story and continuing to bring attention to the issue.
Evolution of Payment & Transactions
Bitcoin Payments get a boost from Coinbase
Coinbase has announced it will support Lightning, the payments network that runs on Bitcoin. Cathie Wood of ARK Invest praised the move. Bitcoin, to date the world's most favored crypto asset, is a Layer 1 blockchain that predates most of the later innovations in payment efficiency. Adding Lightning as a Bitcoin Layer 2 enables Bitcoin to enable faster payments.
Coinbase's decision to put its weight behind Lightning could make Bitcoin a contender for a broader set of payment use cases, at least in parts of the world where populations have limited access to banking services.
PayPal's new stablecoin, launched in August is struggling with adoption, as potential users seem hesitant about what to actually use it for. Paypal claims that the stablecoin enables transactions and transfers with no fees. But you need to read their long fee schedule to find the relatively narrow scenarios that actually do not incur fees.
While the outcome of this experiment is unclear, the playbook that PayPal is using - a private network with a more favorable fee structure for members - could benefit industries that have high levels of financial transfers or transactions. Expect more financial services companies and even industry groups to experiment with this concept.
AI Tech Sector: Regulatory Clouds on the Horizon
RETFound is a new self-supervised learning model that evaluates retinal images for signs of eye disease, heart failure, and Parkinsons'. The groundbreaking solution is just one in a class of GenAI innovations that promise to transform healthcare.
But the path for this - and other AI innovations for regulated industries - may be increasingly tricky, as US regulators and lawmakers struggle to come up to speed on the issues. The US is behind - the EU passed the world's first AI regulations in June. But how far behind?
This week's closed-door session in the US Senate provides a clue. The session and commentary afterward revealed the divergent viewpoints on how to leverage AI's increasingly powerful capabilities while managing their increasingly complex risks.
If the path of crypto regulation is any indicator, it may take some time for lawmakers to turn these divergent viewpoints into coherent laws and agency-level policies for the FDA, SEC, CMS, and the like. Meanwhile, states are moving forward with AI laws of their own.
Lack of Regulatory Clarity may put AI tech sector at risk
Earlier this year investors poured enormous amounts of money into AI stocks with little apparent consideration of when these companies might be able to actually go to market with GenAI-based solutions and build revenue streams capable of providing an ROI.
Some now question the wisdom of these moves and worry the market now is overweight in tech stocks: just 7 stocks comprise 29% of the S&P 500.
These companies may face risks of regulatory dysfunction that impact them two ways:
- Impacts during product design and go to market: unaffordable or unclear approval process.
- Impacts after products and services are on the market: haphazard enforcement actions from federal agencies.
Pragmatic players are focusing on simpler consumer uses of AI that won't need to wait for Washington.
Amazon introduced a set of GenAI tools that will help sellers generate better text for marketing and selling their products.
Stability AI introduces Stable Audio, a text-to-audio GenAI play that lets you generate audio clips from a few text phrases. I tried it out, and it never actually returned an output. (The site kept displaying a message that they are "seeing a lot of traffic". So maybe we'll have better luck next week).
Nature Notes: Turning dumps and disasters into havens
Two notable examples of nature's striking ability to recover.
- The Norman J. Levy Park and Preserve was once a notorious NY Landfill. Here is the story of how the dump became a nature park.
- The area around the Chernobyl nuclear accident site is now teeming with wildlife. The radioactive human-free environment is giving plants and animals a chance to thrive.
Not a license to pollute. But certainly gives you hope!
For Paying Members: Designing your org and job family structure to thrive in the GenAI era
Key insights for organizational planners and talent managers who are thinking about how teams and job families need to evolve over the next 12-24 months.
There’s a lot we don’t know yet about GenAI, but what we do know is that it will redefine the business landscape and work as we know it. It is not too early to start thinking about how this impacts your talent strategy and the families of job positions you manage and hire for in your organization.
Getting started on this requires a strong foundational understanding of what is changing, but also what is staying the same...and becoming even more critical. These elements become the reference points to help you develop your next-generation org and talent strategy.
Armed with this, you will be better prepared for what your company and workforce will face in the next 2-4 years, and able to make better decisions regarding talent strategy, and the job roles that you need to focus on. To do this right we'll have to take a little different way of thinking. Instead of thinking about use cases and what we might do with AI, we're going to deliberately think about what we won't be able to do with AI.