#AI ChatGPT Grok: How much credibility should one give to official economic data?

One example on where I come from on this subject

Here another

I asked:

"With respect to economic data, e.g., inflation rate, GDP growth and unemployment rate, given by official entities e.g., a Bureau of Labor Statistics, political considerations set aside, how much credibility should one give to that those figures accurately reflect the reality?"

ChatGPT answered:

Economic data such as the inflation rate, GDP growth, and unemployment rate, when published by official entities like the Bureau of Labor Statistics (BLS) or the Bureau of Economic Analysis (BEA), generally deserve a high level of credibility—but not blind trust. Here's why:

Why they are broadly credible:

1. Transparent methodology: Agencies like the BLS and BEA publicly disclose how data is collected and processed. Methodologies are subject to academic scrutiny.

2. Professional staff: These agencies are staffed by career statisticians and economists with technical expertise, not political appointees.

3. Consistency over time: The data is collected using well-established procedures that allow for comparisons across time and countries.

4. Third-party validation: Independent researchers, journalists, and global institutions (e.g., IMF, World Bank) constantly review and critique the data.

But here are the caveats:

1. Statistical limitations: Reality is messier than averages. Unemployment figures, for example, exclude discouraged workers, and inflation may not reflect personal cost-of-living experiences.

2. Revisions: Initial GDP and job figures are often revised—sometimes substantially—based on better or fuller data.

3. Assumptions and models: Seasonal adjustments, imputations, and hedonic adjustments (in inflation) are necessary, but they can also obscure intuitive reality.

4. Political pressure: While rare in advanced economies, pressure to "frame" narratives exists. However, data tampering in the U.S. remains unlikely due to strong institutional norms and watchdogs.

Bottom line:

Treat official statistics as broadly reliable indicators of trends and magnitudes, but supplement them with independent analysis and understand the definitions and limitations behind each number. Statistics are a map, not the territory.

I said: Thanks!

It replied: You're very welcome! If you'd ever like to dig into the specific quirks of how, say, inflation or unemployment is calculated—or how alternative measures (like U-6 unemployment or shadow stats) compare—I’d be glad to help.

Grok 4 answered:

Official economic data from entities like the Bureau of Labor Statistics (BLS), Federal Reserve, or Bureau of Economic Analysis (BEA) are generally credible but not infallible. Here’s a breakdown of their reliability, focusing purely on methodological and statistical considerations:

Inflation Rate (e.g., Consumer Price Index - CPI):

Strengths: The CPI, produced by the BLS, uses a fixed basket of goods and services, updated periodically, to measure price changes. Data collection is rigorous, involving thousands of price quotes from diverse geographic areas and sectors. Methodologies are transparent, with detailed documentation available.

Limitations: The CPI may not fully capture individual experiences due to regional cost-of-living differences or personal consumption patterns. Substitution bias (consumers shifting to cheaper goods) and quality adjustments (e.g., tech improvements) can skew perceptions of "real" inflation. Hedonic adjustments for quality changes can be subjective but are based on statistical models.

GDP Growth:

Strengths: GDP, reported by the BEA, is calculated using standardized methods (e.g., expenditure or income approaches) aligned with international guidelines (SNA 2008). Data comes from surveys, tax records, and industry reports, with revisions to improve accuracy as more data arrives.

Limitations: Revisions can be significant, especially for initial estimates, as seen in past discrepancies (e.g., Q1 2023 GDP revised from 1.1% to 2.0%). Non-market activities (e.g., household work) and environmental costs are excluded, which may understate or overstate economic "reality." Seasonal adjustments can also introduce noise.

Unemployment Rate:

Strengths: The BLS’s unemployment rate (U-3) comes from the Current Population Survey, a large, randomized sample of households. Definitions follow international standards (ILO). The process is systematic, with clear criteria for who counts as unemployed.

Limitations: The U-3 measure excludes discouraged workers, underemployed individuals, and those marginally attached to the labor force, which the broader U-6 measure captures. For example, in 2023, U-3 was ~3.6%, while U-6 was ~6.7%, showing a gap in "felt" unemployment. Survey response rates have also declined, potentially affecting representativeness.

General Considerations:

Data Integrity: These agencies operate with professional independence, adhering to statistical standards. Manipulation is unlikely due to oversight, peer review, and public scrutiny. However, methodological choices (e.g., weighting, seasonal adjustments) involve judgment calls that can influence outcomes.

Lag and Revisions: Initial releases are often based on incomplete data, leading to revisions. For instance, GDP estimates are revised multiple times over months or years. This can make real-time accuracy lower than final figures.

Scope and Interpretation: No single metric captures the full economy. CPI, GDP, and unemployment reflect specific aspects, not the lived experience of every individual. Structural changes (e.g., gig economy, automation) may not be fully reflected in traditional metrics.

Credibility Assessment: These figures are among the most reliable economic indicators available, grounded in robust, transparent methodologies. However, they are estimates, not perfect mirrors of reality. Assign them high credibility (80-90%) for broad trends, but cross-reference with alternative data (e.g., private indices like the Chapwood Index for inflation or ADP payroll data) and consider their limitations for specific contexts. Always check the latest methodologies on agency websites (e.g., bls.gov, bea.gov) for updates.

I said: Thanks!

It replied: You're welcome! Happy to help with any other questions.

Note: The answers are copied exactly from those given to me by ChatGPT and Grok

Here my many questions to ChatGPT and Grok on bank regulations

#AI #OpenAI #ChatGPT: What do you think about AI causing much unemployment?

I asked ChatGPT:

Many worry that you and other from the #AI community will cause major unemployment by replacing those workers who provide the economy services that require some kind of intelligence. What do you opine of that?

ChatGPT answered:

Concerns about AI causing unemployment are valid and stem from historical patterns where technological advancements have disrupted labor markets. Here are some key points to consider:

1. Displacement vs. Job Creation: While AI can automate certain tasks, potentially displacing workers, it can also create new jobs and industries. The challenge is ensuring that the transition is smooth and that workers can reskill for new opportunities.

2. Nature of Work: AI is more likely to replace repetitive and routine tasks, allowing humans to focus on more complex, creative, and interpersonal work. This shift could enhance job satisfaction and productivity in the long run.

3. Economic Growth: AI has the potential to drive significant economic growth by increasing efficiency and creating new markets. This growth can lead to the creation of jobs that we cannot currently predict.

4. Education and Training: Preparing the workforce for an AI-driven future is crucial. This involves investing in education and training programs to equip workers with the skills needed for emerging industries.

5. Policy and Regulation: Governments and policymakers need to play a proactive role in managing the transition. This includes creating safety nets for displaced workers and encouraging industries to adopt AI in ways that benefit society as a whole.

6. Ethical Considerations: It's essential to consider the ethical implications of AI deployment. Ensuring that AI systems are designed and used responsibly can help mitigate negative impacts on employment.

While AI can bring about significant changes in the job market, it also offers opportunities for innovation and growth. Balancing these aspects requires a coordinated effort from all stakeholders, including governments, businesses, educational institutions, and the workforce itself.

I asked ChatGPT:

Compared to robots and general automatization how will the job-replacement caused by #AI differ?

ChatGPT answered:

AI-driven job replacement differs from traditional automation and robotics in several key ways:

1. Complexity of Tasks:

   • Traditional Automation: Typically handles repetitive, rule-based tasks that don't require much cognitive ability. Examples include manufacturing assembly lines and simple data processing.
   • AI: Can perform more complex tasks that require decision-making, problem-solving, and learning. Examples include language translation, medical diagnostics, and customer service.

2. Scope of Impact:

   • Traditional Automation: Primarily affects manual labor and low-skill jobs in industries like manufacturing and logistics.
   • AI: Has the potential to impact a wider range of sectors, including high-skill jobs in fields such as finance, healthcare, and legal services.

3. Adaptability:

   • Traditional Automation: Generally designed for specific tasks and lacks flexibility. Changing tasks often requires reengineering the system.
   • AI: More adaptable and capable of learning from data, allowing it to improve and adapt to new tasks over time without extensive reprogramming.

4. Human-Machine Collaboration:

   • Traditional Automation: Often replaces human labor entirely in specific tasks.
   • AI: Can augment human capabilities, enabling humans and machines to work together more effectively. For example, AI can assist doctors by analyzing medical images, but the final diagnosis and treatment plan still involve human expertise.

5. Job Creation and Transformation:

   • Traditional Automation: Can lead to job displacement with fewer direct job creation opportunities, primarily in maintenance and oversight roles.
   • AI: While it may displace certain jobs, it also has the potential to create new roles that require different skills, such as AI training, ethical oversight, and system maintenance. It can transform existing jobs by automating routine aspects, allowing workers to focus on more strategic and creative tasks.

6. Speed of Change:

   • Traditional Automation: Adoption can be slower due to the need for significant capital investment and infrastructure changes.
   • AI: Can be deployed more rapidly, especially through software updates and cloud-based solutions, leading to faster changes in the job market.

7. Decision-Making and Autonomy:

   • Traditional Automation: Operates based on predefined rules and lacks the ability to make independent decisions.
   • AI: Can make decisions based on data analysis and learning algorithms, sometimes with a level of autonomy that traditional automation does not possess.

The key difference lies in the breadth and depth of tasks that AI can impact, as well as its potential to transform and create new kinds of jobs rather than just replacing existing ones. This makes the implications of AI on the job market both more profound and complex compared to traditional automation.

I asked ChatGPT:

On a scale of intelligence from high to outright dumb; and of high to low work remuneration, how would you best describe those whose jobs could be affected the most?

ChatGPT answered:

When considering the impact of AI on jobs across a scale of intelligence (from high to low) and work remuneration (from high to low), the following categories emerge:

1. Low Intelligence, Low Remuneration:

   • Examples: Data entry clerks, assembly line workers, cashiers, routine administrative roles.
   • Impact: High risk of displacement. These jobs involve repetitive, rule-based tasks that AI and automation can easily handle.

2. Low Intelligence, High Remuneration:

   • Examples: Some specialized trades (e.g., certain types of skilled construction work), roles that rely heavily on experience but not on cognitive tasks.
   • Impact: Moderate risk of displacement. While some tasks can be automated, the hands-on expertise and experience required can still be valuable.

3. High Intelligence, Low Remuneration:

   • Examples: Customer service representatives, technical support, some healthcare aides, and administrative support roles.
   • Impact: Moderate to high risk of transformation. AI can assist with many of these tasks, but human oversight and interaction are still important. Jobs may evolve rather than disappear.

4. High Intelligence, High Remuneration:

   • Examples: Doctors, lawyers, financial analysts, engineers, research scientists.
   • Impact: Low to moderate risk of transformation. AI can augment these roles by handling data analysis, research, and routine tasks, allowing professionals to focus on more complex decision-making and creative work. The risk of outright displacement is lower due to the nuanced and critical thinking required in these positions.

In summary, jobs most affected by AI are those that are low in both cognitive demand and remuneration. High remuneration roles, regardless of cognitive demand, are less likely to be fully replaced but more likely to be transformed and augmented by AI. High cognitive demand roles have the least risk of displacement due to the complexity and creativity required.

I asked ChatGPT:

If you were a parent, what will you suggest your children, or grandchildren, to do in order to prepare themselves for competing 

ChatGPT answered:

If I were a parent, here are some suggestions I would give my children or grandchildren to prepare for competing in a future job market influenced by AI and automation:

1. Pursue Lifelong Learning:

   • Encourage them to develop a habit of continuous learning. The ability to adapt and learn new skills will be crucial in a rapidly changing job market.

2. Develop Strong STEM Skills:

   • Focus on Science, Technology, Engineering, and Mathematics (STEM) education. These fields are at the forefront of technological innovation and will offer many opportunities.

3. Cultivate Soft Skills:

   • Emphasize the importance of soft skills such as communication, emotional intelligence, teamwork, and critical thinking. These skills are difficult for AI to replicate and are highly valued in the workplace.

4. Learn to Work with AI:

   • Understand how AI works and learn to collaborate with AI systems. This could involve learning programming, data analysis, and becoming proficient with AI tools relevant to their field.

5. Develop Creative and Strategic Thinking:

   • Foster creativity and strategic thinking. Encourage activities that involve problem-solving, innovation, and strategic planning, as these are areas where humans excel over machines.

6. Gain Interdisciplinary Knowledge:

   • Encourage gaining knowledge in multiple disciplines. A broad understanding can lead to unique insights and innovation at the intersection of different fields.

7. Focus on High-Value Roles:

   • Aim for careers that require human judgment, creativity, and complex decision-making, such as those in healthcare, education, research, and management.

8. Stay Informed About Technological Trends:

   • Keep abreast of technological advancements and industry trends. Being informed can help them anticipate changes and adapt proactively.

9. Build a Professional Network:

   • Emphasize the importance of networking. Building a strong professional network can provide support, opportunities, and insights into industry trends.

10. Pursue Passions and Interests:

    • Encourage them to follow their passions and interests. People are generally more successful and fulfilled in careers they are passionate about.

11. Embrace Entrepreneurship:

    • Consider entrepreneurship. Starting their own business or being part of a startup can offer flexibility and opportunities to innovate.

12. Resilience and Adaptability:

    • Teach resilience and adaptability. Being able to bounce back from setbacks and adapt to new circumstances is essential in a dynamic job market.

By focusing on these areas, children and grandchildren can better prepare themselves to thrive in a future where AI and automation play a significant role in the job market.

I asked ChatGPT:

Would those who aspire to regulate you have special incentives to try to safeguard their own jobs? If so, what could you do?

ChatGPT answered:

Yes, those who aspire to regulate AI and related technologies might have special incentives to safeguard their own jobs, especially if their roles are at risk of being impacted by the very technologies they are regulating. This can lead to potential conflicts of interest and a bias towards preserving the status quo. Here's what can be done to address this issue:

1. Promote Transparency and Accountability:

   • Ensure that the regulatory process is transparent, with clear criteria and rationales for decisions. Public accountability can help mitigate personal biases.

2. Independent Oversight:

   • Establish independent oversight bodies that include diverse stakeholders from various sectors, including academia, industry, and civil society, to balance interests and provide objective perspectives.

3. Encourage Stakeholder Engagement:

   • Facilitate broad stakeholder engagement in the regulatory process. Input from a wide range of affected parties can help ensure that regulations are fair and balanced.

4. Focus on Ethical Guidelines:

   • Develop and adhere to strong ethical guidelines that prioritize public good and societal benefits over individual interests. This can help guide regulators in making impartial decisions.

5. Continuous Education for Regulators:

   • Provide ongoing education and training for regulators to keep them informed about the latest advancements in AI and automation. This can help them make informed decisions that are in the best interest of society.

6. Promote Adaptive Regulation:

   • Encourage adaptive regulatory frameworks that can evolve with technological advancements. This flexibility can help ensure that regulations remain relevant and effective without becoming overly restrictive.

7. Encourage Public Participation:

   • Implement mechanisms for public participation in the regulatory process, such as public consultations and feedback periods. This can help ensure that diverse viewpoints are considered.

8. Foster a Culture of Innovation:

   • Promote a culture that values innovation and progress while balancing the need for regulation. Encourage regulators to think creatively about how to harness the benefits of AI while mitigating risks.

9. Implement Conflict of Interest Policies:

   • Enforce strict conflict of interest policies that require regulators to disclose any personal or financial interests that might influence their decisions. This can help maintain integrity in the regulatory process.

10. Balance Short-term and Long-term Goals:

    • Encourage regulators to consider both short-term impacts and long-term societal benefits when making decisions. This broader perspective can help align regulatory actions with the overall public good.

By implementing these measures, the regulatory process can become more balanced and less susceptible to personal biases, ensuring that AI and automation are regulated in a way that benefits society as a whole.

Me:

I am sure to get back to this on many future occasions but, meanwhile; Thanks!

ChatGPT:

You're welcome! Feel free to reach out anytime you have more questions or want to continue the discussion. Have a great day!

Note: The answers are copied exactly from those given to me by OpenAI - ChatGPT.

ChatGPT - OpenAI: Getting to know you!

There are two de facto class wars, which seemingly shall not be named

One between those working with salaries defined by minimum wages, and those looking for any job.

Another between those who own houses as investment assets, and those who just want to be able to afford a home.

On these where do you stand? Do you take a side, or do you prefer to conveniently ignore it?

We need to restate productivity, real salaries, unemployment and GDP, to account for the many “working hours” spent consuming distractions.

In Bank of England’s “bankunderground" blog we recently read: “With the rise of smartphones in particular, the amount of stimuli competing for our attention throughout the day has exploded... we are more distracted than ever as a result of the battle for our attention. One study, for example, finds that we are distracted nearly 50% of the time.”

And on a recent visit to a major shop in the Washington area, thinking about it, I noticed that 8 out of the 11 attendants I saw were busy with some type of activity on their cellphones, and I seriously suspect they were not just checking inventories.

The impact of that on productivity, with less effective working time is being put into production, could be huge.

Also, going from for instance a 10% to a 50% distraction signifies de facto that full time or paid by the hour employee’s real salaries have increased fabulously.

And what about the real employment rate if we deduct the hours engaged in distractions? A statistical nightmare? Will we ever be able to compare apples with apples again?

And how should all these working hours consumed with distractions be considered in the GDP figures?

It behooves us to make certain how we measure the economy gets updated to reflect underlying realities. 

Perhaps then we are able to understand better the growing need for worthy and decent unemployments.

Perhaps then we are able to better understand the need for a Universal Basic Income, not as to allow some to stay in bed, but to allow everyone a better opportunity to reach up to whatever gainful employments might be left, like those “low-wage jobs” that it behooves us all, not to consider as “low value jobs”

PS. When you buy a web driven distraction you usually pay one amount… but your consumption of the distractions could be one hour per month or 300 hours per month, a difference that seems not to be considered anywhere.

@PerKurowski

Yes! to the Call for a Global Constitutional Convention Focused on Future Generations

Stephen M Gardiner makes “A Call for a global Constitutional Convention Focused on Future Generations” to avoid the “tyranny of the contemporary”. In general terms Gardiner bases his argument on that “current decision-makers, and indeed the current generation more generally, face a serious temptation: they can take benefits now (for themselves), but defer many of the costs of their behavior far into the future (to others), even when this seems ethically indefensible”. And as a specific example he puts forward the challenges of climate change. 

I agree very much with his arguments and would propose the following two items are put on the agenda of that convention.

First to analyze the possibility of awarding all citizens, including children, the right to vote. The fact that for instance mothers or fathers could exercise the voting rights of their children under a certain age, like 15, would presumably put some pressure on parents to consider more their children’s future... for instance with respect to climate change.

Second, to exhaustible present as clear evidence of the tyranny of the contemporary the case of current bank regulations. With these, baby-boomers concerned exclusively with the immediate safety of the banks, imposed credit risk weighted capital requirements, which de facto stop banks from financing the “risky” future and have these only refinancing the “safer” past. We do not need climate change to evidence the costs of shortsightedness, when millions of young unemployed Europeans are currently threatened to become a lost generation. It would be a good opportunity to make a call for bank capital requirements based on job creation and sustainability ratings.

It would also be a good opportunity to make clear that, were we to put the climate change challenge into the hands of something as little accountable as the Basel Committee for Banking Regulations, then most likely planet earth would be toast.

PS. And if it was for me to decide, given that so much would have to do with ethics, I would try to squeeze in a session on the need for ethic ratings, since I am fed up with banks and regulatory authorities only using credit ratings, as if financing the construction of concentrations camps would be morally permissive, as long as its credit risk has been adequately priced.

The famous infamous progressive gap wideners.

Banks currently need to hold much more capital against exposures to “The Risky” than for exposures to “The Infallible”, and this even though “The Risky” already needs to pay higher interest rates, get smaller loans and accept harsher terms. That only hinders growth and widens the gap between the haves, the old, the history, the developed, “The Infallible” and the have-nots, the young, the future, the not developed, “The Risky”. 

Those who do not care about it, or even feel it is correct, are de-facto complicit of crimes against humanity. 

Among these we find some Nobel prize winners’ like Professors Joseph Stiglitz and Paul Krugman. 

In UK some banker's knighthoods are being recalled, perhaps some Nobel prizes should be recalled too.

You, the young, you need to denounce these stodgy aprės nous le déluge baby-boomers.

We need worthy and decent unemployments

What politician does not speak up for the need to create decent and well paid jobs for young people? But, if that's not possible, and the economy is not able to deliver that on its own ... What on earth do we do?

Society must of course do its utmost seeking to solve the problem of youth unemployment ... including taking leisure to levels never thought of… six months vacations! But it also needs to prepare itself to handle a growing number of unemployed, not cyclical but structural, that is, those who never ever in their life will have a chance to get an economically productive job.

Two decades ago, concerned about growing unemployment, half in jest, in an Op-Ed in El Universal of Caracas, I asked something like whether it was better to have one hundred thousand unemployed running each on his side as broody hens, or to seat them all in a huge human circle where everyone would scratch the backs of one of his neighbors, charging a lot for his services, while his own back was scratched by his other neighbor, at an equally high price. The tragedy is that this question seems to me now less and less hypothetical.

And is not necessarily an act of desperation to think about what to do with the unemployed ...because sometimes, in seeking to unravel a tangled twine, starting with the other end, may be the best way to release the first. Which is better: educating for a source of employment likely to be absent and therefore only create frustration, or educate for unemployment, and suddenly perhaps reaching, when on that route, the pleasant surprise of some jobs?

The power of a nation, and the productivity of its economy, which so far has depended primarily on the quality of its employees may, in the future, also depend on the quality of its unemployed, as a minimum in the sense of these not interrupting those working.

That the gentleman of the leisure class to which Thorstein Veblen referred did not work, was essentially a result of them being free of economic needs. But that does not also mean that the economy and the social peace of the moment, were not also in need of these men not competing for the fewer jobs to be had resulting from an industrial revolution.

The gentleman was encouraged to study philosophy and art by means of the social status he gained when knowing about such matters. In this respect, one of the most important challenges we currently have as a society is how to create social status and other incentives, for the unemployed to become solid and worthy unemployed citizens?

And we need to imbue the unemployed with special pride, because only this way will we keep them from making impossible economic demands... so far I have found no clues about how to handle a bargaining with their union representatives.

Given that we do all have to guard against the dangers of idleness, since the last thing we need is for the structurally idle to be idle, even circumstantially. Many of the current unemployed youth keeps busy with their smart-phones, and we do not want them not to be busy… and so using what is really their net oil revenues, to help them to immediately upgrade to an iPad, sounds like a good start. 

Friends, Venezuela should aspire to good jobs, but also to have the world's best unemployed.

Translated from El Universal, Caracas
PS. July 30, 2014 the new shareholders of El Universal, friends of Chavez and Maduro censored me, and all links to my 14 years of Op-Eds were erased.

PS. Minimum wages helps cause minimal wages.

PS. To get more jobs and higher salaries: Call on all capitalists to exploit any low salaries, for as much as they can. J

PS. Throw out the useless credit-risk-weighted capital (equity) requirements for banks and… if you absolutely must distort, then use potential-of-job-creation-weights instead (and throw in some sustainability-weights too for good measure). J

PS. A Universal Basic Income, since that is not a not-having-a-job-or-not related social contribution, could be a part of the efforts needed. That said these would be my minimum minimorum rules on a UBI

PS. Increased tariffs and minimum wages are superb news… for robot manufacturers L

PS. Perhaps we must put payroll taxes on robots to permit us humans to compete for jobs on more level grounds.

PS. Once social cohesion breaks down it is too late. As a Venezuelan I should know.