When approaching complex topics that are difficult to understand, I find that it is essential to include two levels of explanation. The abstract summarizes the concepts and principles at play. The concretes give the details that demonstrate how the concepts and principles present themselves in real-world examples. Arguments that go nowhere tend to get stuck in one without the other. Abstracts without concretes are hand-wavy, and no one can understand what the others are talking about, because they cannot agree on definitions. Concretes without abstracts get lost in the details, and no one can see the forest for the trees. You can often forego offering precise definitions, when you can give examples, which by themselves provide a definition by induction.
Whenever government policies are implemented in the name of consumer protection, we can be sure that it is not consumers being protected, but rather crony industry incumbents. It is presented as a false alternative between government regulation or absence of regulation, when the strongest form of regulation with the greatest degree of consumer protection is the free market, where consumers decide how their dollars are spent. Good products from well-behaving businesses are rewarded. Bad products and ill-behaving businesses are punished, often to extinction. Moreover, when consumers are under-serviced, entrepreneurs enter the market to compete against under-performing incumbents by offering innovative new products and business practices to meet the demand for superior goods and services, often disrupting the status quo. Meanwhile, government regulations necessarily entrench the status quo. “Best practices” can only be best until innovations overtake them, at which time they become obsolete. Government regulations often continue to burden an industry with obsolete practices that prevent innovations from flourishing. Thus, incumbents are protected from agile upstarts.
Net Neutrality is promoted ostensibly to protect consumers from Internet Service Providers (ISPs) throttling traffic to disadvantage competitive “over the top” (OTT) content providers (e.g., Netflix) while favoring the ISP’s own content services (e.g., television in the case of a cable ISP). Another hypothetical straw man is for ISPs to charge customers to enable access to various information services. I would argue that no ISP would pursue such goals, because of the backlash and consequent mass-exodus of customers to the embrace of the ISP’s competition. ISPs would also want to avoid anti-trust concerns. Paranoia about ISP misbehavior disregards the lack of a business case. Net Neutrality was enacted in response to no ISPs actually implementing any anti-competitive traffic management on any significant scale.
Consumers want to preserve a “free and open Internet”—rightly so. ISPs have the practical capability to throttle traffic by origin (content provider), traffic type (e.g., video), or consumption (e.g., data limits for heavy users). They have no practical (cost-effective) mechanism to understand the meaning of the content to selectively filter it. ISPs have only blunt instruments to wield.
Unlike ISPs, content providers (e.g., Netflix, Google, Facebook, Twitter, Cloudflare, GoDaddy) are responsible for “information” services, which fall outside the scope of Net Neutrality for “transmission” by carriers. While ISPs have not attempted to damage a free and open Internet, we have already seen content providers behave very badly toward free speech, since they have the ability to understand the meaning of their content.
- Cloudflare Terminates Service to Neo-Nazi Site: Daily Stormer,
as do Google and GoDaddy
- Conservative And Independent YouTube Channels Hit By Censorship And Demonetization
- Google plans to ‘de-rank’ Russia Today and Sputnik to combat misinformation
- How Apple and Google are censoring the mobile Web by banning Gab from their app stores
- How Facebook, Twitter silence conservative voices online
If a “free and open Internet” is what is desired, censorship, bans, de-platforming, and de-monetization by companies, who are the strongest advocates of Net Neutrality, are certainly antithetical to that aim. What is their real motive?
Content providers enjoy having their traffic delivered to customers worldwide. They only pay for the bandwidth to the networks they are directly connected to. They are not charged for their traffic transiting other networks, while routed to their end users. Content providers obviously like this arrangement, and they want to preserve this status quo (protecting their crony interests).
Without Net Neutrality, although ISPs may not have a business case for charging customers (end users) for differentiated services, they would have a strong business case for providing differentiated services (various levels of higher reliability, low latency, low jitter, and guaranteed bandwidth) to content providers. Improvements in high quality delivery (called “paid prioritization”) would be beneficial to innovative applications that may not be viable today. For example, remote surgery. With paid prioritization, this would motivate content providers to buy connectivity into an ISP’s network to provide higher quality service to their customers, who receive their Internet access from that ISP. Or to otherwise share revenue with the ISP for such favorable treatment of their traffic. The environment becomes much more competitive between content providers, while more revenue would be shared with the ISPs. ISPs would then be motivated to invest more heavily to improve their networks to capture more of this revenue opportunity. Consumers benefit from higher quality services, better networks, and increased competition (differentiation based on quality) among content providers.
Continuing the series on Revolutionizing the Enterprise, where we left off at Sparking the Revolution, I would like to further emphasize immediate opportunities for productive improvements, which do not need to venture into much-hyped speculative technologies like blockchain and artificial intelligence.
In the previous article, I identified communication and negotiation as skills where software agents can contribute superior capabilities to improve human productivity by offloading tedium and toil. Basic elements of this problem can be solved without applying advanced technology like AI. Machine learning can provide additional value by discerning a person’s preferences and priorities. For example, this person is always preferring to reschedule dentist appointments but never reschedules family events to accommodate work. Automating the learning of rules enables the prioritization of activities to be automated, further offloading cognitive load.
In my own work, I wish I had a personal assistant, who could shadow my every move. I want it to record my activities so I can replay them later. I want these activities to be in the most concise and compact form, not only as audio and video. For example, as I execute commands in a bash shell, I want to record the command line arguments, the inputs, and the outputs, so this textual information can be copied to technical documentation. As I point and click through a graphical user interface, I want these events to be described as instructions (e.g., input “John Doe” in the field labeled “Name” and click on the “Submit” button).
With a history of my work in this form, this information will be useful for a number of purposes.
- Someone who pioneers a procedure will eventually need to document it for knowledge transfer. Operating procedures teach others how to accomplish the same tasks by observing how it was done.
- Pair programming is often inconvenient due to team members being located remote from each other and separated by time zones. An activity log can enable two remote workers to collaborate more effectively.
- Context switching between tasks is expensive in terms of organizing one’s thoughts. Remembering what a person was doing, so that they can resume later would save time and improve effectiveness.
The above would be a good starting point for a personal assistant without applying any form of AI or analytics. Then, imagine what might be possible as future enhancements. Procedures can be optimized. Bad habits can be replaced by better ones. Techniques used by more effective workers can be taught to others. Highly repeatable tasks can be automated to remove that burden from humans.
I truly believe the places to begin innovating to revolutionize the enterprise are the mundane and ordinary, which machines have the patience, discipline, and endurance to perform better than humans. More ambitious technological capabilities are good value-adds, but we should start with the basics to establish personal assistants in the enterprise as participants in ordinary work, not as esoteric tools in obscure niches.
[Image credit – Robotics and the Personal Assistant of the Future]
Whenever an organization is faced with challenges that require many people to move in a different direction, change their behavior, adjust their attitudes, or alter their thinking, the first thing that management wants to put in place is leadership. They always believe that with the proper top-down inspiration, instruction, and oversight, it will drive the desired results. They believe this model scales hierarchically.
I don’t believe it’s true of problems for which the organization does not have experience and expertise. The more technical and schedule risk that a project incurs because of greater unknowns, the less helpful project planning is. The ability to plan relies on a degree of analysis and design. Without relevant experience to help speculate on how to implement something, planning must happen in ignorance. The plans are meaningless, because actual implementation experience will likely invalidate those plans and designs. Unfortunately, the natural reaction is to spend more time and effort getting those plans right, as the plan goes off track with execution. The more right you try to make it, the worse that situation becomes, as the organization invests more in a futile activity, and less in activities that actually achieve the result. A “learning organization” is what is needed, not one that assumes it knows (or more importantly “can know”) what it’s doing without having done it yet.
The idea of “spontaneous order” is appealing, but that requires all participants to behave rationally with the right signals, so they can work things out among themselves. In large engineering organizations, this does not seem to work, because the communications channels are too narrow, the number of participants too great, and the volume and complexity of knowledge that must be exchanged is too vast. Individuals become too overwhelmed and cannot keep up. Management structures are inevitably put in place to introduce controls and gatekeepers. Whereas chaos is too noisy and incoherent, the imposition of order destroys knowledge pathways from forming spontaneously.
I’m left wondering if there are methods that facilitate spontaneous order. Autonomy, mastery, and purpose are great motivators in the abstract, but they don’t easily translate into concrete methods and tools. I noticed that Facebook has started implementing a system like khanacademy.org for helping edit location information, where it awards points, badges, and levels. Such systems really do provide users with a motivation to achieve the measured outcome. I’m wondering if gamification is a superior way to achieve outcomes.
We went through a period of vertical integration, where businesses bought up the partners in their supply chain to offer greater efficiency and reliable delivery. We also saw a lot of innovation toward disintermediation, cutting out the middleman. Look at Amazon as an exemplar.
This creates industry giants that are too big to resist political cronyism. That is, they win by buying legislation and regulations that hurt their competition, especially small start-ups who can’t afford compliance or who don’t want to operate like status quo incumbents. However, this also makes these giants easy targets for exploitation, as politicians are just as likely to sell out to powerful voting blocks, such as to push for labor rules or minimum wage raises or health insurance benefits.
What we should learn from Uber, AirBnB, and other gig economy digital services is that the cloud service component of their business model would be the perfect counter move to thwart regulatory enslavement schemes. The actual service providers (car drivers, property lessors, etc.) operate as independent businesses, and they don’t operate as employees. In fact, they are customers of the digital service.
We can extend this business model to its extreme. Imagine a digital service for human resource management, which provides an intermediation service between any corporation to workers who operate as independent contractors. The entire concept of employees disappears, as the HRM service provides administrative and labor procurement functions to the purchaser of labor, while simultaneously providing the administrative and labor supply functions that enable the suppliers of labor to operate as independent corporations.
Whereas the voluntary employer-employee relationship has been susceptible to regulatory interference due to the historical power of labor unions, the integrity of private contracts is sacrosanct, and will be very difficult for legislators and regulators to impair, as it will be vigorously defended and upheld in the courts.
While I am not a climate scientist and do not claim to have any special expertise in climate research, my interest is to analyze how a layman should organize his thoughts around this complex topic so that critical thinking can be applied to separate truth from propaganda and political posturing.
We have seen the media and leading voices on the topic of climate change promote the following ideas:
- Climate Change is Settled Science and How Climate Deniers Try to Sow Confusion
- Labeling climate change skeptics as “science deniers”
The term “denial” conflates healthy skepticism over extraordinary claims with the non-recognition of scientific facts that are largely beyond dispute. Extraordinary claims are certainly under dispute by experts in their fields, and the disingenuous label of “denial” is intended to chill skepticism, a hallmark of science, with authoritarian dogma (“settled science” is the antithesis of science). Here is a sampling of dissent:
- It’s Said That ‘97% of Climate Scientists Agree’ About Global Warming – But Do They?
- What I Learned about Climate Change: The Science is not Settled
- 49 Former NASA Scientists Send A Letter Disputing Climate Change
- The Truth About Climate Change
- My Global Warming Skepticism, for Dummies
- Aliens Cause Global Warming – a CalTech lecture by Michael Crichton
The case being made by the climate change activists contains several elements:
- Global temperatures have been rising at an alarming rate since the beginning of the industrial revolution. This is where science investigates the facts through measurements that are indisputable except for accuracy, error, and methods to ensure that the data is true. Unfortunately, even at this fundamental level certain scientists have exhibited misbehavior (Climategate), such as data manipulation, lack of transparency of unaltered data sets, what those data alterations were, exclusion of participants from peer review, exclusion of participants from publications, and suppression of dissent. While such misbehavior undermines the credibility of the science, on net the evidence does support the position that global temperatures have risen 1.2°C since the pre-industrial era.
- Warming is predominantly caused by increased CO2 concentrations in the atmosphere. The strongest argument in favor of attributing the cause of warming to CO2, as opposed to solar activity and any number of variables that affect the phenomena under measurement (e.g., proxies to temperature such as tree rings are sensitive to many factors like sunlight, rainfall, soil conditions, nutrients, and pestilence which cannot be separated from the effects of temperature), is the observation that surface temperatures have risen as lower stratospheric temperatures have dropped, which is predicted if greenhouse warming due to CO2 is the cause.
- Warming is unprecedented and unnatural. This is where science can provide insights into historical events and patterns. Articles such as Nature Unbound III: Holocene climate variability (Part A) and Part B give some perspective into natural trends over millennia that show large temperature variations and atmospheric CO2 levels that are natural and uncorrelated.
- Rising atmospheric CO2 levels are the result of emissions from burning fossil fuels, and therefore human activity is to blame. There can be little dispute that the post-industrial rise in atmospheric CO2 is primarily attributable to human activity.
- Elevated atmospheric CO2 levels and associated warming are bad. Melting glaciers, rising sea levels, increases in extreme weather events, disruptions of ocean currents, ocean acidification, and even mass extinctions are potential hazards that climate alarmists are warning of. These claims are strongly disputed    . Measuring a global trend and determining the cause are problematic. On the other hand, there is a fair amount of research that suggests that global warming has been beneficial.
- Global Warming Produced a Greener, More Fruitful Planet
- CO2-induced Greening of the Earth: Benefiting the Biosphere While Lifting the Poor out of Poverty – “Typically, a doubling of the air’s CO2 content above present-day concentrations raises the productivity of most herbaceous plants by about one-third; this positive response occurs in plants that utilize all three of the major biochemical pathways of photosynthesis.”
- Greener, Not Browner – “We show a persistent and widespread increase of growing season integrated LAI (greening) over 25% to 50% of the global vegetated area, whereas less than 4% of the globe shows decreasing LAI (browning). Factorial simulations with multiple global ecosystem models show that CO2 fertilization effects explain 70% of the observed greening trend…”
- The Impact of Global Warming on Health and Mortality – “Since heat-related deaths are generally much fewer than cold-related deaths, the overall effect of global warming on health can be expected to be a beneficial one.”
- Rising atmospheric CO2 levels and warming trend will be catastrophic. Predictions of catastrophic levels of warming are based on climate models, which have had a very poor track record to date. Models have made predictions that do not comport with observations.
- Summer Arctic ice in the North Pole did not completely disappear by 2013, as Al Gore predicted.
- 18 spectacularly wrong predictions made around the time of the first Earth Day in 1970, expect more this year
- Climate Alarmists Have Been Wrong About Virtually Everything
- Even the IPCC (1990) stated: “The climate system is a coupled non-linear chaotic system, and therefore the long-term prediction of future climate states is not possible.”
- Intervention is required to curtail human activity that emits CO2.
- Government policies are the proper means of intervention.
- The specific policies being advocated are the best solutions to prevent catastrophe and provide the best net benefit.
By the time we reach the final three claims about solutions, we must have already drawn conclusions from the previous six that global warming is catastrophic and predominantly caused by CO2 emissions from human activities. Any critical examination of the evidence would not support such a conclusion. The case for climate alarmism falls apart at the third claim. The evidence favors the Lukewarmers, “those who argue that carbon dioxide indeed is warming surface temperatures, but that its effect is modest and that we are inadvertently adapting”. However, let’s roll with the “hotheads” to see where they want to lead us.
When exploring practical solutions, we move beyond scientific research into the realm of engineering, which is applied science. How to solve the problem can either be compatible with liberty – relying on voluntary action; or the solutions can rely on coercion and force through government action. This falls into the political realm.
When evaluating how best to deploy scarce resources (e.g., labor, factors of production, capital investment) among various alternative solutions, we move beyond the physical sciences into the realm of economics, which is a social science. Humans cannot be treated as inanimate objects without free will, rationality, and rights.
Government policies cannot be implemented without expecting people to resist, avoid, or bypass them. Policies cannot anticipate how human ingenuity and innovation can provide better solutions; or how policies may impair such solutions from being developed, as crony regulations that protect incumbents and government “picking winners” have a tendency to do.
Government funding of scientific research has conflicts of interest. You tend to get the results that you pay for, because researchers understand that their funding will only continue if the government’s favored outcomes are achieved and their policy goals are supported.
Government funding of their preferred solutions results in cronyism. Let’s examine green energy subsidies. Here are some examples:
- Obama clean energy loans leave taxpayers in $2.2 billion hole
- President Obama’s Taxpayer-Backed Green Energy Failures
If climate change advocates cared about practical solutions to replacing CO2 emitting energy generation, they would support modern and future nuclear power technologies. This topic is explored in the article titled What are some policies that would improve millions of lives, but people still oppose?
What climate alarmists leave unsaid is their aim to scale back human activity to reduce the impact on the environment. It is a greater priority to preserve wilderness than to improve the standard of living for humans. People have no right to exist in their world view.
The popular movement against climate change is not primarily about science. Its main aim is political advocacy. That is, scientific arguments are used to support the political lobbying for government mandated economic solutions to future problems that are predicted by models based on the scientific explanations of physical phenomena that contribute to climate. In the realm of political debate and economics, the physical sciences are just a useful idiot, where cherry-picked results are used to promote the preferred policy goals. Popular opinion is driven by the desired political outcome, not by the truth of the science. Their goal is to shift power away from individuals seeking to improve their standard of living, and concentrating power in governments to implement collectivist policies that are used to implement cronyism and corruption.
This article is a derivation of the concept of rights from first principles. This is the notion of natural rights consistent with The Jeffersonian Perspective. Throughout this article, I shall use the term “man” to refer to a human being, not to gender.
Man exists as a being of a certain nature, which is distinctly different than other beings. Man is a living being with the unique ability to reason. Man relies on his ability to reason for survival.
For man to exist qua man, as a living reasoning being according to his nature, certain conditions must exist. Man’s rationality is conditional upon being free to think and act according to his reasoning mind. Freedom is the absence of coercion and force from other men. The mind is impotent when man is threatened or attacked with the force of violence.
Rights are based on the mutual recognition of man’s nature and the conditions required for man’s survival. Rights are the mutual respect for freedom of thought and action so that man can exist according to his nature.
In my previous article, Revolutionizing the Enterprise, I provided an outlook for how emerging technologies may help to transform how we do work. Now, let’s explore how we might provide the spark that starts the fire to burn down the old and welcome the new. The world does not change in a radical way without a progression of steps that pave a path for getting from here to there. What might the first step be to introducing robots and AIs as personal assistants into the regular work lives of numerous employees?
We need only look to our daily struggles to identify where every person would see the value of machine intelligence. Organizing a meeting among several participants can be challenging. You need to find a convenient time when every participant is available. You need to find a suitable venue that can accommodate everyone. If folks need to travel, the complexity rises enormously, because each traveler’s attendance is then dependent upon successfully booking travel arrangements. The risk of a single unsatisfied requirement causing the meeting to be non-viable rises with each participant and their special needs. If the meeting needs to be moved to accommodate certain participants, this would then trigger a storm of activity to renegotiate, and a flurry of activity to explore how calendars can be readjusted with a cascade of renegotiations of other appointments, each having its own priority and constraints.
This kind of negotiation among a network of people is virtually impossible to accomplish by humans among each other, because of the latency for human communications. However, if every human could be represented by an agent, who could negotiate on their behalf, this kind of activity could become painless. Imagine how many hours of phone tag, email, and travel booking could be saved. Even if an agent were not entrusted to finalize decisions on travel booking, all of the negotiation and arrangements could be prepared and presented for final approval by the human; or even involve the human at key decision points by presenting a short list of options to guide the way forward for the agent.
I believe, ordinary mundane problems such as this one, which every person has experienced, will serve as an opportunity to introduce machine intelligence to work alongside us. The off-loading of such unproductive and non-creative toil to an automated personal assistant would be a welcome change that would be seen as another useful tool, rather than a radical development. And that’s how the revolutionary should begin.
It has been over five years since I wrote an article titled Enterprise Collaboration, in which I identified the need for innovations to transform how people do their work. Since then, we have seen no significant advances. Enterprise applications continue to move very slowly to the cloud, driven primarily by cost efficiencies with little noticeable functional improvement except at the margins (big data analytics, social, search, mobile, user experience).
Where can we go from here?
I still firmly believe that a global work force needs to be decoupled in space and time. Mobility and cloud services will continue to provide an improving platform to enable work to be performed at any time from wherever people want. We should enable people to do their work as effectively from the office as from home, in their vehicles, during air travel, at the coffee shop, or anywhere else they happen to be. Advances in computing power, miniaturization, virtual reality, alternative display and input technologies (e.g., electronic skin, heads up displays, voice recognition, brain computer interfaces, etc.), and networking will continue to provide an improving platform for inventing better ways of doing work and play. This path does not need too much imagination to foresee.
Recently, we have seen an up-tick in applying artificial intelligence. Every major company seems to be embracing AI in some form. Image recognition and natural language are areas that have been researched for decades, and they are now being employed more ubiquitously in every day applications. These technologies lower the barrier between the virtual world and the real world, where humans want to interact with machine intelligence on their own terms.
However, I believe an area where AI will provide revolutionary benefits is in decision support and autonomous decision-making. So much of what people do at work is tedium that they wish could be automated. Some forms of tedium are drudgery, such as reporting status and time to management, organizing and scheduling meetings among team members, planning work and tracking progress, and keeping people informed. These tasks are routine and time-consuming, not creative and value-producing. Machines can interact among themselves to negotiate on behalf of humans for the most mundane tasks that people don’t really care too much to be involved in. Machines can slog through an Internet full of information to gather, prune, and organize the most relevant set of facts that drive decisions. Machines can carry out tasks on their own time, freeing up humans to work on more important or interesting things.
Personal assistants as computing applications are a new phenomenon. Everyone has heard of Amazon Echo and Google Assistant by now. I can imagine advances in this capability expanding into all areas of work and personal life to help off-load tedium. As AI becomes more capable, we should see them taking over mundane tasks, like research (e.g., comparing products to offer recommendations toward a purchasing decision, comparing providers toward recommending a selection), planning, coordinating, note taking, recalling relevant information from memory, distilling large volumes of information into a concise summary, etc. Eventually, AI will even become capable enough to take over mundane decision-making tasks that a person no longer cares to make (e.g., routinely replenish supplies of consumables from the lowest priced supplier, repetitive tasks).
The other phenomenon that will revolutionize the work place even more than in the past is robotics. Robots have already revolutionized manufacturing for decades by replacing repetitive error-prone labor-intensive tasks with perfectly reproducible error-free automation. We are seeing politics influence businesses to apply robots, where human labor sufficed in the past, purely because of the increasing cost of labor. Minimum wage legislation (bans on jobs that pay less than some mandated floor in wages) that raises labor costs above the value produced will force businesses to rethink how to operate profitably. Beyond entry-level jobs, such as fast food service, self-driving cars and trucks are already in trials for ride-sharing and long haul cargo transport. As robots become more dexterous, mobile, compact, and intelligent, we will see them become personal assistants to perform physical tasks as much as we see them in software form perform computing tasks. We should anticipate that robots will serve in a broad spectrum of capacities from low-skilled drudgery to highly-skilled artisans and professions.
The future enterprise will involve a work force where humans, AIs, and robots collaborate closely. Humans have a comparative advantage in performing creative and path-finding tasks with ill-defined goals, many unknowns, and little experience to draw upon. Robots and AIs have a comparative advantage in performing repetitive, well-defined, and tedious tasks. Together, they will transform the enterprise in ways that we have never seen before.
Here is Ben’s theory about the impossibility of black hole and big bang singularities.
I think once we understand the Higgs mechanism better, we will discover that above a certain temperature, which rises as we work backward in time to make the universe more dense, the opposite of “condensation” happens. The bosons no longer have mass. No mass, no gravity; no longer contributing gravity means the very force that is squeezing things together stops squeezing at the core. I believe this should put a limit on how dense things can be, so it is impossible to form a singularity, if you cannot pass this density limit at the extreme interior.
I wish I knew a lick of math, so I could even comprehend what SU(2) × U(1) means. Sadly, I’ll have no chance of writing a paper and winning a Nobel prize. Math is hard.