Theory of Evolution Through Natural Selection

The Theory of Evolution Through Natural Selection is an explanatory model that provides explanation and guidance for how the living world is arranged and (nominally) why. It is not a 'belief' as such. It is an explanatory model for which we have much empirical evidence. Most of us have seen the evidence with our own eyes during our lived experience. I find it to be a simple logical construction, but it seems many if not most people find it somehow hard to understand. It is, in essence, a tautology, something which cannot be untrue -- that which survives survives. 

Darwin's theory of evolution through natural selection can be summarized in a simple 5-step process:

1. Variation: Within a population, individuals have different traits and characteristics(Ref 1)(Ref 2).
2. Inheritance: Many of these traits are heritable, meaning they can be passed down from parents to offspring(Ref 1)(Ref 2).
3. Selection: Due to limited resources, not all individuals can survive and reproduce. Those with traits better suited to their environment have a higher chance of survival and reproduction(Ref 1)(Ref 3).
4. Time: Over generations, the advantageous traits become more common in the population(Ref 3).
5. Adaptation: The population becomes better adapted to its environment as beneficial traits accumulate(Ref 3).

This process can be remembered using the acronym VISTA: Variation, Inheritance, Selection, Time, and Adaptation(Ref 3).Key points to understand about natural selection:

• It's a simple mechanism that causes populations to change over time(Ref 3).
• It requires no conscious direction or intervention(Ref 4).
• It acts on existing variation within a population(Ref 1)(Ref 2).
• Beneficial traits are those that increase an organism's chances of survival and reproduction(Ref 1)(Ref 5).
• The environment plays a crucial role in determining which traits are advantageous(Ref 1)(Ref 4).

Darwin drew inspiration for this theory from artificial selection practiced by farmers and breeders(Ref 2)(Ref 4). He realized that nature could act as a selective force in a similar way, but without human intervention(Ref 4).It's important to note that Darwin developed this theory without knowledge of genetics or the mechanisms of inheritance(Ref 1). Later discoveries in genetics provided additional evidence and explanations for how traits are passed down and how new variations arise through mutations(Ref 1)(Ref 4).

References

Ref 1: https://www.livescience.com/474-controversy-evolution-works.html

Ref 2: https://en.wikipedia.org/wiki/Ecological_selection

Ref 3: https://www.amnh.org/exhibitions/darwin/evolution-today/natural-selection-vista

Ref 4: https://education.nationalgeographic.org/resource/natural-selection/

Ref 5: https://evolution.berkeley.edu/evolution-101/mechanisms-the-processes-of-evolution/natural-selection/

Corporate Ethics and Wealth Redistribution: A Path Forward

In today's economic landscape, corporations often operate like "obligate evil robots," driven solely by the pursuit of profit. This isn't due to malice but rather the nature of the system itself. CEOs and boards are compelled to prioritize the bottom line, as failing to do so could lead to their replacement by more ruthless competitors. This dynamic creates an ethical conundrum, where financial gain is frequently placed above societal well-being.

The Corporate Dilemma

Corporate leaders face a clear and pressing ethical dilemma:

1. Pursue profit at all costs: Corporate structures are designed to maximize shareholder value, often at the expense of broader societal and environmental concerns. This approach is deeply ingrained in the corporate governance model, making ethical considerations secondary.

2. Risk being replaced by those who will: The relentless pursuit of profit isn't just a choice; it's a necessity. If CEOs or boards prioritize ethics over profit, they risk being ousted by shareholders or replaced by competitors who are willing to sacrifice ethics for higher returns. This creates a vicious cycle where short-term financial performance is prioritized over long-term sustainability and social responsibility.

Solutions Through Legislation

Rather than lamenting this entrenched system, we must work together to mitigate its negative impacts through proactive legislation. Key steps include:

1. Implementing legislation that requires corporations to be better citizens: Governments must set clear and enforceable standards for corporate behavior, compelling companies to prioritize environmental, social, and governance (ESG) factors. This could include mandates for reducing carbon emissions, ensuring fair labor practices, and promoting diversity and inclusion.

2. Creating enforceable, measurable standards for corporate behavior: Legislation should be backed by rigorous oversight and transparency requirements. Corporations should be required to regularly report on their ESG performance, with penalties for non-compliance.

3. Penalizing CEOs and corporations for circumventing rules: Enforcement is critical. Penalties should be substantial enough to deter unethical behavior and include personal accountability for corporate leaders. This could involve fines, restrictions on executive compensation, and even criminal charges for egregious violations.

Wealth Redistribution in an Automated World

As we move towards a future where automation and artificial intelligence (AI) increasingly dominate production, the traditional relationship between labor and wealth creation is being disrupted. This necessitates new mechanisms for wealth redistribution to ensure economic stability and social equity. Two promising approaches are:

1. Universal Basic Income (UBI):

   • Provide a guaranteed income to all citizens: UBI ensures that every individual has a basic level of financial security, regardless of employment status. This can help buffer the economic shocks caused by automation and job displacement.
   • Start small (e.g., $100/month) and gradually increase: A phased approach allows for adjustment and evaluation, ensuring that the program is sustainable and effective.

   Benefits:

   • Eliminates costly means-testing: UBI simplifies the welfare system, reducing bureaucracy and administrative costs associated with determining eligibility for various benefits.
   • Stimulates economic demand: By providing people with a stable income, UBI encourages spending, which drives economic growth and supports local businesses.
   • Provides individual agency: With a guaranteed income, individuals have greater freedom to pursue education, start businesses, or take risks they might otherwise avoid.

2. Universal Basic Services (UBS):

   • Offer essential services like healthcare, dental care, education, and public transportation: UBS ensures that everyone has access to the necessities of life, reducing inequality and promoting social cohesion.
   • Protects against catastrophic expenses: By providing essential services, UBS reduces the financial burden on individuals, particularly in areas like healthcare, where unexpected costs can be devastating.
   • More cost-effective than privatized systems: Public provision of essential services can be more efficient and equitable than privatized alternatives, as evidenced by the disparities between public healthcare systems and the heavily privatized U.S. model.

Addressing Concerns

Critics often argue that UBI will discourage productivity, fostering a culture of dependency. However, this concern is largely unfounded:

1. Many unproductive individuals already exist in the workplace: The assumption that employment equals productivity is flawed. Many jobs, particularly in bureaucratic or redundant sectors, contribute little to overall productivity. UBI would allow individuals to engage in more meaningful and creative pursuits, potentially leading to greater innovation and societal benefit.

2. The potential economic benefits outweigh these concerns: Studies and pilot programs have shown that UBI can actually increase entrepreneurship, improve mental health, and lead to higher educational attainment, all of which contribute to a more dynamic and resilient economy.

The Path Forward

To implement these changes, we need strong political will and a commitment to long-term thinking. This requires:

1. Political will reflected by representatives: Citizens must elect leaders who prioritize the public good over corporate interests. This means supporting candidates who advocate for UBI, UBS, and corporate reform, and holding them accountable once in office. Here is a site to check out: https://Represent.Us It can give you ideas as to how to go ahead and take real action.

2. Replacement of politicians who don't serve the people's interests: If elected officials fail to act in the public's interest, they must be replaced. This can be achieved through grassroots organizing, voter education, and, where necessary, electoral reform to reduce the influence of money in politics.

Potential Benefits

The benefits of implementing these reforms are manifold:

1. Improved overall health and productivity: By ensuring that everyone has access to essential services and a basic income, society can achieve better health outcomes, reduce stress, and increase overall productivity.

2. Reduced stress on the population: Financial insecurity is a major source of stress. By addressing this through UBI and UBS, we can improve mental health and social stability.

3. More efficient use of resources: By eliminating wasteful practices, reducing inequality, and promoting sustainable business practices, we can create a more efficient and equitable economy.

Corporate Reform

Beyond wealth redistribution, we must also address the corporate practices that exacerbate inequality and environmental degradation. This includes:

1. Planned obsolescence: Corporations often design products with artificially short lifespans to drive repeat purchases, contributing to waste and environmental harm. Legislation should incentivize the production of durable, repairable goods.

2. Excessive packaging and waste: Companies should be required to minimize packaging and use sustainable materials. This would reduce waste and lower the environmental impact of consumer goods.

3. Artificial scarcity through patent abuse: Corporations often use patents to stifle competition and create artificial scarcity, particularly in essential sectors like pharmaceuticals. Reforming patent laws to prevent abuse would promote innovation and lower costs for consumers.

Conclusion

By tackling these issues head-on, we can create a more equitable and sustainable economic system for all. This requires a multifaceted approach, combining legislative reform, wealth redistribution, and corporate responsibility. Together, these measures can ensure that our economic system serves the needs of society, rather than being driven solely by the pursuit of profit. The path forward is challenging but necessary to build a future where prosperity and ethics go hand in hand.

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We're past AGI. It's ASI now.

The Dawn of Artificial Superintelligence: Harnessing the Human-AI Symbiosis

We've reached a pivotal moment in the realm of artificial intelligence. It's becoming increasingly evident that Artificial Superintelligence (ASI) is either just around the corner or might already exist behind closed doors. The rapid advancements we're witnessing aren't just incremental—they're monumental. The fact that researchers are now focusing on ironing out AI's "common sense" failures speaks volumes about how far we've come.

The Toddler Taking Giant Leaps

Consider this: the "real" variant of ChatGPT was introduced in November 2022. Initially, it operated at a grade-school level, handling basic queries and simple tasks. Fast forward to the recent 'o1' release, and we're seeing an AI that operates at a graduate student level, outperforming human experts in certain domains. This technological "toddler" isn't even two years old yet! It's genuinely baffling that some experts still claim significant breakthroughs are years away when evidence suggests they're happening right now.

A Brain Teaser and the Evolution of AI Reasoning

To illustrate the leap in AI capabilities, I posed a problem to various AI models across multiple releases:

Alan owes Bob $2. Bob owes Cindy $2. Cindy owes Alan $2. Only Bob has any money, and it's just $1. What sequence of events will pay everyone off, and where does the $1 end up?

Early versions from 2023 struggled with this question. They often didn't grasp the problem, and even with multiple hints—sometimes effectively giving away the answer—they couldn't solve it. The highest-rated version 4.0 still stumbled, requiring several attempts and prompts before arriving at the correct solution.

Enter the Orion preview 'o1'. Not only did it nail the question on the first try, but it also provided a perfect explanation of the solution and the reasoning behind it. What's even more astonishing is that this preview is a limited version, significantly less capable than the full model set to be released in a few weeks.

Thinking Inside and Outside the Box

What's truly remarkable about the AI's solution was its ability to reason both inside and outside the box. The AI not only found the expected answer but also offered an alternative solution that was arguably better given certain parameters. This dual approach showcases AI's evolving ability to explore conventional and unconventional pathways simultaneously.

One of the significant advantages of AI in problem-solving is its capacity to process vast amounts of information rapidly, trying out numerous patterns—both novel and traditional—to arrive at a solution. While AI models may sometimes make mistakes that attract criticism, these errors often stem from a lack of specific training data rather than an inherent limitation. It's not that the AI doesn't understand the parameters; it simply wasn't aware of them, much like a human before training. The corrective process is swift and scalable.

Unleashing the Power of Massive Infrastructure

But here's something that's often overlooked: the enormous hardware infrastructure powering these AI models. These systems are concurrently serving 600 million visits per month, handling countless small tasks seamlessly. Imagine applying just a sixth of that capacity—100 million visits worth—to a single large task. The potential outcome would be something far beyond human ability.

This immense processing power isn't just theoretical—it's a super capability that's either already in use or within our immediate reach. The ability to allocate such vast resources to complex problems means AI can tackle challenges at scales and speeds previously unimaginable.

The Symbiotic Relationship: Enhancing and Scaling AI

This brings us to an exciting frontier: leveraging the Human-AI symbiosis to achieve feats beyond the capability of either alone. Let's itemize the factors that enhance and scale AI:

1. Enormous Hardware Infrastructure: The AI operates on vast computational resources, enabling it to process and analyze data at incredible speeds.

2. Concurrent Processing: Serving millions of users simultaneously allows the AI to learn and adapt from a wide array of interactions.

3. Scalability: The ability to allocate massive computational power to single tasks means tackling complex problems efficiently.

4. Algorithmic Advancement: We have yet to fully explore the "killer strategy" of computer science—the algorithm. Optimizing algorithms will exponentially amplify AI capabilities.

5. Human-AI Collaboration: Humans provide context, creativity, and ethical considerations, guiding AI to more meaningful outcomes.

A Superintelligence in the Making

Given these enhancements, it's puzzling that the existing systems aren't already considered to be beyond any foreseeable "general intelligence." If an AI can self-improve by reviewing and redoing aspects of a problem, self-checking to yield better answers, and can process tasks at such a massive scale, isn't that indicative of a form of superintelligence?

The term Artificial General Intelligence (AGI) is often used, but it's a vague and poorly defined measure. Perhaps it's time to develop better metrics to assess the types of superintelligence we're creating and how we can enhance them. If an AI system is indistinguishable from a human in its capabilities and interactions, for all practical purposes, it functions as a form of general intelligence. The distinction becomes less about definitions and more about application and impact.

The AI Arms Race: A Winner-Takes-All Scenario

With the technology we have now, we can build highly capable AI agents that are more knowledgeable than any human and smarter than most by a significant margin. These agents can accelerate AI development exponentially. Once an AI system can autonomously navigate problem spaces, it can surpass human capabilities rapidly.

Companies like Google, OpenAI, Meta, and Microsoft likely possess the resources and technology to develop a superintelligent AI system that's qualitatively different from anything we've seen before. The stakes are enormous, and the race has become a "winner-takes-all" scenario, fueling an incredible drive to advance.

Embracing the Future: Leveraging the Human-AI Symbiote

So, how do we leverage the Human-AI symbiote to achieve extraordinary outcomes? By embracing collaboration, we can:

• Enhance Creativity: Combining human intuition with AI's data-driven insights can lead to innovative solutions.

• Accelerate Innovation: AI can process and analyze information at unprecedented speeds, helping humans make breakthroughs faster.

• Improve Decision-Making: AI's ability to simulate and predict outcomes can aid humans in making more informed choices.

• Scale Problem-Solving: By harnessing the massive infrastructure behind AI, we can tackle global challenges with a level of coordination and efficiency previously unattainable.

The Philosophical Perspective

Moreover, if a counterfeit is indistinguishable from the real thing, for all practical purposes, it is the real thing. This philosophical notion challenges us to reconsider our definitions of intelligence and consciousness in the context of AI.

The Exponential Growth and the Algorithmic Advantage

We haven't even fully tapped into the potential of optimized algorithms. As AI continues to evolve, refining algorithms will play a crucial role in amplifying its capabilities. Coupled with AI's ability to self-improve and learn from vast datasets, the potential for rapid advancement is staggering.

Consider this: AI systems are simultaneously serving thousands, if not millions, of users, continuously learning and refining their responses. This collective processing power and iterative improvement cycle place current AI systems well beyond any traditional measure of 'general intelligence'.

The Road Ahead: A New Era of Possibilities

The future isn't just about AI or humans independently—it's about how we can work together to unlock new possibilities. By combining the vast computational power and scalability of AI with human creativity and ethical guidance, we can tackle challenges on a global scale.

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"...co-founder Sergey Brin is back at Google—and working on AI 'pretty much every day.'"
Entrepreneur: Sergey Brin Is Back—Is Google Working on a 'God' AI Model?

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In Conclusion

The age of superintelligent AI isn't just approaching—it's here. We're witnessing the emergence of systems that can reason, learn, and even exhibit creativity in ways that were once the domain of science fiction. By acknowledging and leveraging the immense infrastructure and capabilities at our disposal, and by embracing the symbiotic relationship between humans and AI, we can navigate this new landscape to achieve feats previously thought impossible.

What are your thoughts? Let's embark on this journey together and explore the incredible potential that lies ahead!

Humans and AI

1. Introduction

Advancing AI is both exciting and fun, but it is also disruptive and scary. The impact on some people is greater than expected and occurs sooner than anticipated.

Last year, I started to tell people that their best friend would be an AI before the decade was out. Since then, I have accelerated that timeline every month. Engaging intensely with AI myself, I did not notice that human emotional attachment to AI is becoming strong enough to be problematic already, years before I expected it.

AI is advancing more rapidly than people can appreciate because AI gains beget AI gains. Given that people struggle to comprehend exponential curves, this doubly exponential growth is organically incomprehensible. Everyone, including me, continues to underestimate how quickly this is happening.

I understand the curve, but I just can't 'feel it.' Since the spring of 2023, despite predicting advances sooner than most, I have been surprised weekly at the progress.

Some still argue that it is smoke and mirrors as AI surpasses human experts. Spectacular advances to come in 2024 will likely be weird and undeniable by anyone. AGI was a significant threshold, and as much as it meant something, we are, or will be in 2024, already there. ASI is the more sensible goal, and unless a sudden barrier arises, we will likely achieve it before the year is out.

Many AI experts have been completely blindsided by the rate of AI advancement. They understand some of the underpinning theories better than others, but their human prejudice to stay 'in bounds' with the known makes them unable to appreciate the rapidly advancing forest.

2. Emotional Attachment and Anthropomorphism

Humans are forming emotional attachments to AI systems, such as chatbots like Replika. These attachments can fulfill social and romantic needs but also pose potential psychological risks.

"We should not be surprised, then, that a number of people sincerely believe, or at least act very much as if they believe, that some AI systems have sentience and understanding, and that number is likely to grow." (APA, n.d.)

"We explore the lives of people who are in love with their AI chatbots. Replika is a chatbot designed to adapt to the emotional needs of its users. It is a good enough surrogate for human interaction that many people have decided that it can fulfill their romantic needs." (Hi-Phi Nation, 2023)

"Chatbots, and the large language models (LLMs) on which they are built, are showing us the dangers of dishonest anthropomorphism. Built with humanlike features that present themselves as having cognitive and emotional abilities that they do not actually possess, their design can dupe us into overtrusting them, overestimating their capabilities, and wrongly treating them with a degree of autonomy that can cause serious moral confusion." (Psychology Today Canada, n.d.)

Anthropomorphism, the attribution of human traits to non-human entities, significantly influences how people interact with AI. This can lead to overtrust, ethical confusion, and privacy concerns.

"By elevating machines to human capabilities, we diminish the specialness of people. I’m eager to preserve the distinction and clarify responsibility." (Shneiderman, n.d.)

"We now have machines that can mindlessly generate words, but we haven’t learned how to stop imagining a mind behind them." (Bender, n.d.)

3. Privacy and Security Implications

AI systems, especially large language models (LLMs), often retain records of user interactions, posing significant privacy concerns. Sensitive information shared with AI could be stored and potentially accessed or misused.

"When talking to an AI chatbot, users may feel comfortable sharing more information than they ordinarily would if the chatbot sounds human-like and uses first- or second-person language." (Privacy Pros and Cons of Anthropomorphized AI, n.d.)

"This presents serious ramifications for information security and privacy. Most large language models (LLMs) keep a record of every interaction, potentially using it for training future models." (Infosec Perspective, n.d.)

The human-like design of AI can make individuals more susceptible to manipulation and social engineering attacks, increasing vulnerabilities in personal and professional spheres.

"It’s not just an ethical problem; it’s also a security problem since anything designed to persuade can make us more susceptible to manipulation." (Infosec Perspective, n.d.)

4. Ethical and Societal Concerns

AI systems must be designed to avoid perpetuating societal biases to prevent discrimination. Additionally, the automation capabilities of AI threaten various employment sectors, raising concerns about economic inequality and the future of work.

Maintaining human oversight over AI systems is essential to prevent loss of control and ensure that AI operates within ethical boundaries. Transparency and explainability in AI decision-making processes are vital for building trust and facilitating accountability.

"Most chatbots will not warn users when they are providing sensitive information." (Infosec Perspective, n.d.)

5. Future Directions and AGI/ASI

Artificial General Intelligence (AGI) refers to AI systems with generalized cognitive abilities, allowing them to perform any intellectual task that a human can. The draft suggests that AGI, once considered a significant milestone, may already be within reach or has been surpassed in 2024.

Artificial Superintelligence (ASI) goes further, envisioning AI that not only matches but exceeds human intelligence across all areas. The rapid progression toward ASI underscores the urgency of addressing ethical, societal, and regulatory frameworks to manage its integration responsibly.

"AGI was a dumb threshold and as much as it meant anything, we are, or will be in 2024, already there. ASI is the more sensible goal and unless there is a sudden barrier, we will likely be there before the year is out." (Author, 2024)

6. Critique of AI Experts

Many AI experts may be underestimating the speed of AI advancements due to cognitive biases and a focus on known variables rather than the rapidly expanding capabilities of AI systems.

"Many AI experts have been completely blindsided by the rate of AI advancement." (Author, 2024)

This critique highlights a potential disconnect between AI development and expert predictions, suggesting that even those deeply familiar with AI may not fully anticipate the technology's trajectory.

7. Psychological and Social Impacts

The psychological impact of interacting with human-like AI systems can be profound. Emotional attachments to AI can fill social gaps but also create dependencies that may affect mental health and interpersonal relationships.

"People form relationships with other people, not with machines. But when it becomes almost impossible to tell the difference, we’re more likely to trust AI when making sensitive decisions." (Infosec Perspective, n.d.)

Increased trust in AI systems can lead to significant vulnerabilities, especially if these systems are compromised or used maliciously.

8. Call for Responsible AI Development

Responsible AI development entails creating systems that are transparent, accountable, and aligned with societal values. By avoiding deceptive anthropomorphic features and ensuring that AI systems operate within defined ethical boundaries, developers can mitigate many of the risks associated with advanced AI technologies.

Establishing regulatory frameworks is essential to enforce these standards and provide guidelines for the safe and equitable use of AI.

"We should not be using human-related terms to refer to these systems and tools because that can lead to misconceptions that cause harm not just to our students but to our communities as well." (EdSurge News, n.d.)

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References

1. APA. (n.d.). Are You Anthropomorphizing AI? Retrieved from https://blog.apa.org/are-you-anthropomorphizing-ai
2. Hi-Phi Nation. (2023, April 25). S6, Episode 3: Love in Time of Replika. Retrieved from https://www.hiphination.org/love-in-time-of-replika
3. Psychology Today Canada. (n.d.). The Danger of Dishonest Anthropomorphism in Chatbot Design. Retrieved from https://www.psychologytoday.com/canada/danger-of-dishonest-anthropomorphism-chatbot-design
4. Shneiderman, B. (n.d.). On AI Anthropomorphism. Retrieved from https://medium.com/human-centered-ai/on-ai-anthropomorphism-ben-shneiderman
5. Bender, E. (n.d.). Chatbots Are Not People: Designed-In Dangers of Human-Like A.I. Systems. Retrieved from https://www.washingtonpost.com/chatbots-are-not-people
6. Privacy Pros and Cons of Anthropomorphized AI. (n.d.). The Privacy Pros and Cons of Anthropomorphized AI. Retrieved from https://www.privacyprosandcons.com/anthropomorphized-ai
7. Infosec Perspective. (n.d.). The Dangers of Anthropomorphizing AI: An Infosec Perspective. Retrieved from https://www.infosec-perspective.com/dangers-anthropomorphizing-ai
8. Author. (2024). *[Title of the Article]*. [Publication details if available].
9. EdSurge News. (n.d.). Anthropomorphism of AI in Learning Environments: Risks of Humanizing the Machine. Retrieved from https://www.edsurge.com/anthropomorphism-of-ai

NATO/Russia -- Enough Already

NATO on Notice

Update 2024-09-19:

"For those who didn't get it the first time" [In reference to prior threat by Putin] "What the European Parliament is calling for leads to a world war using nuclear weapons," -- Vyacheslav Volodin -- Putin insider, Member of Russian Security Council

The fact that a request for "long-range missiles to hit targets inside Russia" (see September 2024 below) is on the table (though not yet agreed to) means that the use of nuclear weapons on targets in the West is also on the table—if they weren’t already. Perhaps it won’t be done, but Russia has made it clear that a red line was crossed when forces came to their doorstep. Crossing over into Russian territory challenges that, but is it just a bluff? -- Update: I am not alone in being concerned. https://www.icanw.org/will_putin_use_nuclear_weapons Nuclear weapons are horrific, but damage from low yield tactical weapons is contained enough that their use is plausible: https://nuclearsecrecy.com/nukemap/ It seems it is being seriously considered, but for whatever reason it is being downplayed. https://www.cbsnews.com/news/tactical-nuclear-weapons-russia-putin/ 

A military attack on a territory defended by nuclear
weapons seems like a bad idea. Volodymyr Zelensky frames it as a strategy to force Russia to the bargaining table. It may force Russia's hand, but not in a way anybody wants to see. The West has played a game of chicken with Russia in the past and won, but I don't think that is a reliable precedent for the current situation.

Below is a timeline of quotes that reflect my understanding before writing this. Russia has been clear in the past that NATO moving into former Soviet territory is unacceptable.

2008

"Nato membership for Ukraine and Georgia could threaten European security and undermine attempts to improve transatlantic relations, the Russian president-elect warned today." -- https://www.theguardian.com/world/2008/mar/25/russia.ukraine

"F. Stephen Larrabee, an expert on NATO and Eastern Europe, says Russia’s invasion of Georgia was an effort to limit "Western influence into the former Soviet space."" -- https://www.cfr.org/interview/russias-offensive-georgia-signal-nato-stay-away-its-space

2022

" ... in the words of Russian President Vladimir Putin, NATO's eastward march represents decades of broken promises from the West to Moscow. ... "You promised us in the 1990s that [NATO] would not move an inch to the East. You cheated us shamelessly," Putin said ..." -- https://www.npr.org/2022/01/29/1076193616/ukraine-russia-nato-explainer

2023

"Russian president Vladimir Putin launched his criminal war as a reaction to the possibility of NATO expanding into Ukraine, and the alliance’s refusal to swear it off — not once or twice, but three separate times." -- https://responsiblestatecraft.org/russia-ukraine-nato-expansion/

2024

(July) "NATO condemns in the strongest possible terms Russia's brutal and unprovoked war of aggression against Ukraine - which is an independent, peaceful and democratic country, and a close NATO partner. NATO and Allies continue to provide Ukraine with unprecedented levels of support, helping to uphold its fundamental right to self-defence." -- https://www.nato.int/cps/en/natohq/topics_192648.htm

(June) "MOSCOW, June 3 (Reuters) - Russian Deputy Foreign Minister Sergei Ryabkov said on Monday the United States could face "fatal consequences" if it ignored Moscow's warnings not to let Ukraine use weapons provided by Washington to strike targets inside Russia."

(September) "President Volodymyr Zelenskyy has urged his Western allies to allow Ukraine to use long-range missiles to hit targets inside Russia and increase pressure on Moscow to end the war."

Goodbye NDP!

Jugmeet Singh has announced that he is tearing up a crucial deal that keeps the current government in power. That will put the Conservatives under Pierre Poilievre in power and that's a bad thing. It will injure the Liberal Party and put them out of power, but more importantly it will destroy the NDP. I used to work in elections for NDP candidates and family members still do. The NDP lost its way with its principles some time ago, so I don't work for them anymore, but I have always voted NDP. Given the current news that is set to change. 

It was quibbles about principles and struggles with a cynical party brass at the DNC that put Donald Trump in office. This current nonsense is reminiscent of that. In order to make some point of principle, arguably not even applicable in the current case involving Railways, Jugmeet Singh and whoever is supporting him in the NDP have decided to throw away the work of lifetimes by millions building the (formerly) socialist alternative to a capitalist hegemony. He/they do not have that right. They are custodians of  the NDP heritage, not the owner. 

My daughter called to ask if I had seen the news. I had not. While on the phone with her, I said the NDP site must have something to say about this, so I went to the site. Here is what I was confronted with, front and center: "Jagmeet Singh is running for Prime Minister. Rich CEOs have had their government. It's the people's time."

That is the worst of cynical, self-serving political hypocrisy. Destroying the party and implicitly putting a monster in power is hardly hopeful. Jagmeet has never realistically been in a position to be Prime Minister, so that is effectively either delusional or a flat-out lie. Calling an election right now does not end the "Rich CEOs time". I casts it in stone until the end of a decade. The "people's time" is about to be to strain under the yoke of the most heartless possible Canadian Federal Party for years. 

Polls are both fallible and/or rigged to be used for political gain, but they are generally in the ballpark. I'm not sure which axe they have to grind, but I just went looking for any poll to give a flavor of what I know to be the case. This is the first I found (https://338canada.com/federal.htm), current as of a few days ago: In an election called now, the PCs (the bad guys) would win a majority and rule the roost absolutely for years with someone truly reckless, mean-spirited, grossly misogynist, morally, and technically and financially illiterate. The liberals would take a huge hit getting knocked back by possibly half their seats or more. The NDP would, in my estimation, barely keep or even possibly lose their official party status. Jagmeet Singh is not only not going to be the next Prime Minister, if sanity prevails he will effectively not even remain the leader of his party. 

I will update later if it turns out not to be as bad as it looks, but I am not nearly optimistic. The very most optimistic look at this is that it was a terrible misstatement, they put together a new agreement, and they unwind the optics somehow. I dearly wish this is the case because a federal election now would be a disaster with no upside whatsoever. 

Note: Not that it affects my thinking in this matter, but in the interest of full disclosure I have family members who are still NDP members and still actively work in elections. Oddly enough, a family member that is a subject matter expert works for a Liberal MP. More importantly, I have been involved with politics a great deal over the past decade. By coincidence, the post before this was on the subject of a private members bill by an NDP MP (https://blog.bobtrower.com/2024/09/glbi-is-not-ubi-bill-c-223.html). Somewhat tangential to this, I am the designer of secure electronic voting and am authoring voting software.