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Gennady Stolyarov II and Tobias Teufel Discuss Science, Technology, Politics, and Transhumanism

Gennady Stolyarov II and Tobias Teufel Discuss Science, Technology, Politics, and Transhumanism

Tobias Teufel
Gennady Stolyarov II


On July 9, 2019, U.S. Transhumanist Party Chairman Gennady Stolyarov II conversed with Tobias Teufel, a transhumanist from Germany and Allied Member of the U.S. Transhumanist Party, regarding a variety of subjects – including a comparison / contrast of the voting systems in Germany and the United States, robotics, 3D printing, space colonization, life extension, possibilities for persuading those who are reluctant to accept emerging technologies, as well as some thoughts that Mr. Teufel had in connection with the recent First Virtual Debate of the U.S. Transhumanist Party’s Presidential primary candidates. Overall, Mr. Teufel shared some excellent insights regarding technological possibilities – including many that are open to ordinary people today – and some promising ways in which the Transhumanist Party can continue to reach out and educate the public about ongoing technological advances and their uses. Watch the conversation on YouTube here.

Become a member of the U.S. Transhumanist Party / Transhuman Party for free, no matter where you reside. Apply here in less than a minute.

Gennady Stolyarov II Interviews Ray Kurzweil at RAAD Fest 2018

Gennady Stolyarov II Interviews Ray Kurzweil at RAAD Fest 2018

Gennady Stolyarov II
Ray Kurzweil


The Stolyarov-Kurzweil Interview has been released at last! Watch it on YouTube here.

U.S. Transhumanist Party Chairman Gennady Stolyarov II posed a wide array of questions for inventor, futurist, and Singularitarian Dr. Ray Kurzweil on September 21, 2018, at RAAD Fest 2018 in San Diego, California. Topics discussed include advances in robotics and the potential for household robots, artificial intelligence and overcoming the pitfalls of AI bias, the importance of philosophy, culture, and politics in ensuring that humankind realizes the best possible future, how emerging technologies can protect privacy and verify the truthfulness of information being analyzed by algorithms, as well as insights that can assist in the attainment of longevity and the preservation of good health – including a brief foray into how Ray Kurzweil overcame his Type 2 Diabetes.

Learn more about RAAD Fest here. RAAD Fest 2019 will occur in Las Vegas during October 3-6, 2019.

Become a member of the U.S. Transhumanist Party for free, no matter where you reside. Fill out our Membership Application Form.

Watch the presentation by Gennady Stolyarov II at RAAD Fest 2018, entitled, “The U.S. Transhumanist Party: Four Years of Advocating for the Future”.

Review of Frank Pasquale’s “A Rule of Persons, Not Machines: The Limits of Legal Automation” – Article by Adam Alonzi

Review of Frank Pasquale’s “A Rule of Persons, Not Machines: The Limits of Legal Automation” – Article by Adam Alonzi

Adam Alonzi


From the beginning Frank Pasquale, author of The Black Box Society: The Secret Algorithms That Control Money and Information, contends in his new paper “A Rule of Persons, Not Machines: The Limits of Legal Automation” that software, given its brittleness, is not designed to deal with the complexities of taking a case through court and establishing a verdict. As he understands it, an AI cannot deviate far from the rules laid down by its creator. This assumption, which is not even quite right at the present time, only slightly tinges an otherwise erudite, sincere, and balanced coverage of the topic. He does not show much faith in the use of past cases to create datasets for the next generation of paralegals, automated legal services, and, in the more distant future, lawyers and jurists.

Lawrence Zelanik has noted that when taxes were filed entirely on paper, provisions were limited to avoid unreasonably imposing irksome nuances on the average person. Tax-return software has eliminated this “complexity constraint.” He goes on to state that without this the laws, and the software that interprets it, are akin to a “black box” for those who must abide by them. William Gale has said taxes could be easily computed for “non-itemizers.” In other words, the government could use information it already has to present a “bill” to this class of taxpayers, saving time and money for all parties involved. However, simplification does not always align with everyone’s interests. TurboTax’s business, which is built entirely on helping ordinary people navigate the labyrinth is the American federal income tax, noticed a threat to its business model. This prompted it to put together a grassroots campaign to fight such measures. More than just another example of a business protecting its interests, it is an ominous foreshadowing of an escalation scenario that will transpire in many areas if and when legal AI becomes sufficiently advanced.

Pasquale writes: “Technologists cannot assume that computational solutions to one problem will not affect the scope and nature of that problem. Instead, as technology enters fields, problems change, as various parties seek to either entrench or disrupt aspects of the present situation for their own advantage.”

What he is referring to here, in everything but name, is an arms race. The vastly superior computational powers of robot lawyers may make the already perverse incentive to make ever more Byzantine rules ever more attractive to bureaucracies and lawyers. The concern is that the clauses and dependencies hidden within contracts will quickly explode, making them far too detailed even for professionals to make sense of in a reasonable amount of time. Given that this sort of software may become a necessary accoutrement in most or all legal matters means that the demand for it, or for professionals with access to it, will expand greatly at the expense of those who are unwilling or unable to adopt it. This, though Pasquale only hints at it, may lead to greater imbalances in socioeconomic power. On the other hand, he does not consider the possibility of bottom-up open-source (or state-led) efforts to create synthetic public defenders. While this may seem idealistic, it is fairly clear that the open-source model can compete with and, in some areas, outperform proprietary competitors.

It is not unlikely that within subdomains of law that an array of arms races can and will arise between synthetic intelligences. If a lawyer knows its client is guilty, should it squeal? This will change the way jurisprudence works in many countries, but it would seem unwise to program any robot to knowingly lie about whether a crime, particularly a serious one, has been committed – including by omission. If it is fighting against a punishment it deems overly harsh for a given crime, for trespassing to get a closer look at a rabid raccoon or unintentional jaywalking, should it maintain its client’s innocence as a means to an end? A moral consequentialist, seeing no harm was done (or in some instances, could possibly have been done), may persist in pleading innocent. A synthetic lawyer may be more pragmatic than deontological, but it is not entirely correct, and certainly shortsighted, to (mis)characterize AI as only capable of blindly following a set of instructions, like a Fortran program made to compute the nth member of the Fibonacci series.

Human courts are rife with biases: judges give more lenient sentences after taking a lunch break (65% more likely to grant parole – nothing to spit at), attractive defendants are viewed favorably by unwashed juries and trained jurists alike, and the prejudices of all kinds exist against various “out” groups, which can tip the scales in favor of a guilty verdict or to harsher sentences. Why then would someone have an aversion to the introduction of AI into a system that is clearly ruled, in part, by the quirks of human psychology?

DoNotPay is an an app that helps drivers fight parking tickets. It allows drivers with legitimate medical emergencies to gain exemptions. So, as Pasquale says, not only will traffic management be automated, but so will appeals. However, as he cautions, a flesh-and-blood lawyer takes responsibility for bad advice. The DoNotPay not only fails to take responsibility, but “holds its client responsible for when its proprietor is harmed by the interaction.” There is little reason to think machines would do a worse job of adhering to privacy guidelines than human beings unless, as mentioned in the example of a machine ratting on its client, there is some overriding principle that would compel them to divulge the information to protect several people from harm if their diagnosis in some way makes them as a danger in their personal or professional life. Is the client responsible for the mistakes of the robot it has hired? Should the blame not fall upon the firm who has provided the service?

Making a blockchain that could handle the demands of processing purchases and sales, one that takes into account all the relevant variables to make expert judgements on a matter, is no small task. As the infamous disagreement over the meaning of the word “chicken” in Frigaliment v. B.N.S International Sales Group illustrates, the definitions of what anything is can be a bit puzzling. The need to maintain a decent reputation to maintain sales is a strong incentive against knowingly cheating customers, but although cheating tends to be the exception for this reason, it is still necessary to protect against it. As one official on the  Commodity Futures Trading Commission put it, “where a smart contract’s conditions depend upon real-world data (e.g., the price of a commodity future at a given time), agreed-upon outside systems, called oracles, can be developed to monitor and verify prices, performance, or other real-world events.”

Pasquale cites the SEC’s decision to force providers of asset-backed securities to file “downloadable source code in Python.” AmeriCredit responded by saying it  “should not be forced to predict and therefore program every possible slight iteration of all waterfall payments” because its business is “automobile loans, not software development.” AmeriTrade does not seem to be familiar with machine learning. There is a case for making all financial transactions and agreements explicit on an immutable platform like blockchain. There is also a case for making all such code open source, ready to be scrutinized by those with the talents to do so or, in the near future, by those with access to software that can quickly turn it into plain English, Spanish, Mandarin, Bantu, Etruscan, etc.

During the fallout of the 2008 crisis, some homeowners noticed the entities on their foreclosure paperwork did not match the paperwork they received when their mortgages were sold to a trust. According to Dayen (2010) many banks did not fill out the paperwork at all. This seems to be a rather forceful argument in favor of the incorporation of synthetic agents into law practices. Like many futurists Pasquale foresees an increase in “complementary automation.” The cooperation of chess engines with humans can still trounce the best AI out there. This is a commonly cited example of how two (very different) heads are better than one.  Yet going to a lawyer is not like visiting a tailor. People, including fairly delusional ones, know if their clothes fit. Yet they do not know whether they’ve received expert counsel or not – although, the outcome of the case might give them a hint.

Pasquale concludes his paper by asserting that “the rule of law entails a system of social relationships and legitimate governance, not simply the transfer and evaluation of information about behavior.” This is closely related to the doubts expressed at the beginning of the piece about the usefulness of data sets in training legal AI. He then states that those in the legal profession must handle “intractable conflicts of values that repeatedly require thoughtful discretion and negotiation.” This appears to be the legal equivalent of epistemological mysterianism. It stands on still shakier ground than its analogue because it is clear that laws are, or should be, rooted in some set of criteria agreed upon by the members of a given jurisdiction. Shouldn’t the rulings of law makers and the values that inform them be at least partially quantifiable? There are efforts, like EthicsNet, which are trying to prepare datasets and criteria to feed machines in the future (because they will certainly have to be fed by someone!).  There is no doubt that the human touch in law will not be supplanted soon, but the question is whether our intuition should be exalted as guarantee of fairness or a hindrance to moving beyond a legal system bogged down by the baggage of human foibles.

Adam Alonzi is a writer, biotechnologist, documentary maker, futurist, inventor, programmer, and author of the novels A Plank in Reason and Praying for Death: A Zombie Apocalypse. He is an analyst for the Millennium Project, the Head Media Director for BioViva Sciences, and Editor-in-Chief of Radical Science News. Listen to his podcasts here. Read his blog here.

Why Robots Won’t Cause Mass Unemployment – Article by Jonathan Newman

Why Robots Won’t Cause Mass Unemployment – Article by Jonathan Newman

The New Renaissance Hat
Jonathan Newman
August 5, 2017
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I made a small note in a previous article about how we shouldn’t worry about technology that displaces human workers:

The lamenters don’t seem to understand that increased productivity in one industry frees up resources and laborers for other industries, and, since increased productivity means increased real wages, demand for goods and services will increase as well. They seem to have a nonsensical apocalyptic view of a fully automated future with piles and piles of valuable goods everywhere, but nobody can enjoy them because nobody has a job. I invite the worriers to check out simple supply and demand analysis and Say’s Law.

Say’s Law of markets is a particularly potent antidote to worries about automation, displaced workers, and the so-called “economic singularity.” Jean-Baptiste Say explained how over-production is never a problem for a market economy. This is because all acts of production result in the producer having an increased ability to purchase other goods. In other words, supplying goods on the market allows you to demand goods on the market.

Say’s Law, Rightly Understood

J.B. Say’s Law is often inappropriately summarized as “supply creates its own demand,” a product of Keynes having “badly vulgarized and distorted the law.”

Professor Bylund has recently set the record straight regarding the various summaries and interpretations of Say’s Law.

Bylund lists the proper definitions:

Say’s Law:

  • Production precedes consumption.
  • Demand is constituted by supply.
  • One’s demand for products in the market is limited by one’s supply.
  • Production is undertaken to facilitate consumption.
  • Your supply to satisfy the wants of others makes up your demand for for others’ production.
  • There can be no general over-production (glut) in the market.

NOT Say’s Law:

  • Production creates its own demand.
  • Aggregate supply is (always) equal to aggregate demand.
  • The economy is always at full employment.
  • Production cannot exceed consumption for any good.

Say’s Law should allay the fears of robots taking everybody’s jobs. Producers will only employ more automated (read: capital-intensive) production techniques if such an arrangement is more productive and profitable than a more labor-intensive technique. As revealed by Say’s Law, this means that the more productive producers have an increased ability to purchase more goods on the market. There will never be “piles and piles of valuable goods” laying around with no one to enjoy them.

Will All the Income Slide to the Top?

The robophobic are also worried about income inequality — all the greedy capitalists will take advantage of the increased productivity of the automated techniques and fire all of their employees. Unemployment will rise as we run out of jobs for humans to do, they say.

This fear is unreasonable for three reasons. First of all, how could these greedy capitalists make all their money without a large mass of consumers to purchase their products? If the majority of people are without incomes because of automation, then the majority of people won’t be able to help line the pockets of the greedy capitalists.

Second, there will always be jobs because there will always be scarcity. Human wants are unlimited, diverse, and ever-changing, yet the resources we need to satisfy our desires are limited. The production of any good requires labor and entrepreneurship, so humans will never become unnecessary.

Finally, Say’s Law implies that the profitability of producing all other goods will increase after a technological advancement in the production of one good. Real wages can increase because the greedy robot-using capitalists now have increased demands for all other goods. I hope the following scenario makes this clear.

The Case of the Robot Fairy

This simple scenario shows why the increased productivity of a new, more capital-intensive technique makes everybody better off in the end.

Consider an island of three people: Joe, Mark, and Patrick. The three of them produce coconuts and berries. They prefer a varied diet, but they have their own comparative advantages and preferences over the two goods.

Patrick prefers a stable supply of coconuts and berries every week, and so he worked out a deal with Joe such that Joe would pay him a certain wage in coconuts and berries every week in exchange for Patrick helping Joe gather coconuts. If they have a productive week, Joe gets to keep the extra coconuts and perhaps trade some of the extra coconuts for berries with Mark. If they have a less than productive week, then Patrick still receives his certain wage and Joe has to suffer.

On average, Joe and Patrick produce 50 coconuts/week. In exchange for his labor, Patrick gets 10 coconuts and 5 quarts of berries every week from Joe.

Mark produces the berries on his own. He produces about 30 quarts of berries every week. Joe and Mark usually trade 20 coconuts for 15 quarts of berries. Joe needs some of those berries to pay Patrick, but some are for himself because he also likes to consume berries.

In sum, and for an average week, Joe and Patrick produce 50 coconuts and Mark produces 30 quarts of berries. Joe ends up with 20 coconuts and 10 quarts of berries, Patrick ends up with 10 coconuts and 5 quarts of berries, and Mark ends up with 20 coconuts and 15 quarts of berries.

Production Trade Consumption
Joe 50 Coconuts (C) Give 20C for 15B 20C + 10B
Patrick n/a 10C + 5B (wage)
Mark 30 qts. Berries (B) Give 15B for 20C 20C + 15B

The Robot Fairy Visits

One night, the robot fairy visits the island and endows Joe with a Patrick 9000, a robot that totally displaces Patrick from his job, plus some. With the robot, Joe can now produce 100 coconuts per week without the human Patrick.

What is Patrick to do? Well, he considers two options: (1) Now that the island has plenty of coconuts, he could go work for Mark and pick berries under a similar arrangement he had with Joe; or (2) Patrick could head to the beach and start catching some fish, hoping that Joe and Mark will trade with him.

While these options weren’t Patrick’s top choices before the robot fairy visited, now they are great options precisely because Joe’s productivity has increased. Joe’s increased productivity doesn’t just mean that he is richer in terms of coconuts, but his demands for berries and new goods like fish increase as well (Say’s Law), meaning the profitability of producing all other goods that Joe likes also increases!

Option 1

If Patrick chooses option 1 and goes to work for Mark, then both berry and coconut production totals will increase. Assuming berry production doesn’t increase as much as coconut production, the price of a coconut in terms of berries will decrease (Joe’s marginal utility for coconuts will also be very low), meaning Mark can purchase many more coconuts than before.

Suppose Patrick adds 15 quarts of berries per week to Mark’s production. Joe and Mark could agree to trade 40 coconuts for 20 quarts of berries, so Joe ends up with 60 coconuts and 20 quarts of berries. Mark can pay Patrick up to 19 coconuts and 9 quarts of berries and still be better off compared to before Joe got his Patrick 9000 (though Patrick’s marginal productivity would warrant something like 12 coconuts and 9 quarts of berries or 18 coconuts and 6 quarts of berries or some combination between those — no matter what, everybody is better off).

Production Trade Consumption
Joe 100C Give 40C for 20B 60C + 20B
Patrick 45B n/a 16C + 7B (wage)
Mark Give 20B for 40C 24C + 18B

Option 2

If Mark decides to reject Patrick’s offer to work for him, then Patrick can choose option 2, catching fish. It involves more uncertainty than what Patrick is used to, but he anticipates that the extra food will be worth it.

Suppose that Patrick can produce just 5 fish per week. Joe, who is practically swimming in coconuts pays Patrick 20 coconuts for 1 fish. Mark, who is excited about more diversity in his diet and even prefers fish to his own berries, pays Patrick 10 quarts of berries for 2 fish. Joe and Mark also trade some coconuts and berries.

In the end, Patrick gets 20 coconuts, 10 quarts of berries, and 2 fish per week. Joe gets 50 coconuts, 15 quarts of berries, and 1 fish per week. Mark gets 30 coconuts, 5 quarts of berries, and 2 fish per week. Everybody prefers their new diet.

Production Trade Consumption
Joe 100C Give 50C for 15B + 1F 50C + 15B + 1F
Patrick 5 fish (F) Give 2F for 20C + 10B 20C + 10B + 2F
Mark 30B Give 25B for 30C + 1F 30C + 5B + 2F

Conclusion

The new technology forced Patrick to find a new way to sustain himself. These new jobs were necessarily second-best (at most) to working for Joe in the pre-robot days, or else Patrick would have pursued them earlier. But just because they were suboptimal pre-robot does not mean that they are suboptimal post-robot. The island’s economy was dramatically changed by the robot, such that total production (and therefore consumption) could increase for everybody. Joe’s increased productivity translated into better deals for everybody.

Of course, one extremely unrealistic aspect of this robot fairy story is the robot fairy. Robot fairies do not exist, unfortunately. New technologies must be wrangled into existence by human labor and natural resources, with the help of capital goods, which also must be produced using labor and natural resources. Also, new machines have to be maintained, replaced, refueled, and rejiggered, all of which require human labor. Thus, we have made this scenario difficult for ourselves by assuming away all of the labor that would be required to produce and maintain the Patrick 9000. Even so, we see that the whole economy, including the human Patrick, benefits as a result of the new robot.

This scenario highlights three important points:

(1) Production must precede consumption, even for goods you don’t produce (Say’s Law). For Mark to consume coconuts or fish, he has to supply berries on the market. For Joe to consume berries or fish, he has to supply coconuts on the market. Patrick produced fish so that he could also enjoy coconuts and berries.

(2) Isolation wasn’t an option for Patrick. Because of the Law of Association (a topic not discussed here, but important nonetheless), there is always a way for Patrick to participate in a division of labor and benefit as a result, even after being displaced by the robot.

(3) Jobs will never run out because human wants will never run out. Even if our three island inhabitants had all of the coconuts and berries they could eat before the robot fairy visited, Patrick was able to supply additional want satisfaction with a brand new good, the fish. In the real world, new technologies often pave the way for brand new, totally unrelated goods to emerge and for whole economies to flourish. Hans Rosling famously made the case that the advent of the washing machine allowed women and their families to emerge from poverty:

And what’s the magic with them? My mother explained the magic with this machine the very, very first day. She said, “Now Hans, we have loaded the laundry. The machine will make the work. And now we can go to the library.” Because this is the magic: you load the laundry, and what do you get out of the machine? You get books out of the machines, children’s books. And mother got time to read for me. She loved this. I got the “ABC’s” — this is where I started my career as a professor, when my mother had time to read for me. And she also got books for herself. She managed to study English and learn that as a foreign language. And she read so many novels, so many different novels here. And we really, we really loved this machine.

And what we said, my mother and me, “Thank you industrialization. Thank you steel mill. Thank you power station. And thank you chemical processing industry that gave us time to read books.”

Similarly, the Patrick 9000, a coconut-producing robot, made fish production profitable. Indeed, when we look at the industrial revolution and the computer revolution, we do not just see an increase in the production of existing goods. We see existing goods increasing in quantity and quality; we see brand new consumption goods and totally new industries emerging, providing huge opportunities for employment and future advances in everybody’s standard of living.

Jonathan Newman is Assistant Professor of Economics and Finance at Bryan College. He earned his PhD at Auburn University and is a Mises Institute Fellow. He can be contacted here.

The Good News They’re Not Telling You – Article by Thomas E. Woods, Jr.

The Good News They’re Not Telling You – Article by Thomas E. Woods, Jr.

The New Renaissance HatThomas E. Woods, Jr.
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As we look at things that impress us technologically we also have a certain trepidation, because we’re told that robots are going to take our jobs. “Yes, the internet is wonderful,” we may say, “but robots, I don’t want those.”

I don’t mean to make light of this because robots are going to take a lot of jobs. They’re going to take a lot of blue collar jobs, and they’re going to take a lot of white collar jobs you don’t think they can take. Already there are robots that can dispense pills at pharmacies. That’s being done in California. They have not made one mistake. You can’t say that about human pharmacists, who are now free to be up front talking to you while the robot fills the prescription.

Much of this is discussed by author Kevin Kelly in his new book The Inevitable, with the subtitle Understanding the 12 Technological Forces that Will Shape Our Future. It’s incredible what robots can do and what they will be able to do.

Automation Really Is Taking Our Jobs

To me, just the fact that one of Google’s newest computers can caption a photo perfectly — it can figure out what’s happening in the photo and give a perfect caption — is amazing. Just when you think “a machine can’t do my job,” maybe it can.

What kind of world is this we’re moving into? I understand the fear about that. But, at the same time, let’s think, first of all, about what happened in the past.

In the past, most people worked on farms, and automation took away 99 percent of those jobs. Literally 99 percent. They’re gone. People wound up with brand new jobs they could never have anticipated. And in pursuing those jobs we might even argue that we became more human. Because we diversified. Because we found a niche for ourselves that was unique to us. Automation is going to make it possible for human beings to do work that is more fulfilling.

How is that? Well, first let’s think about the kinds of jobs that automation and robots do that we couldn’t do even if we tried. Making computer chips, there’s no one in this room who could do that. We don’t have the precision and the control to do that. We can’t inspect every square millimeter of a CAT scan to look for cancer cells. These are all points Kevin Kelly is trying to make to us. We can’t inflate molten glass into the shape of a bottle.

So, there are many tasks that are done by robots, through automation that are tasks we physically could not do at all, and would not get done otherwise.

Automation Creates Luxuries We Didn’t Know Were Possible

But also automation creates jobs we didn’t even know we wanted done. Kelly gives this example:

Before we invented automobiles, air-conditioning, flat-screen video displays, and animated cartoons, no one living in ancient Rome wished they could watch pictures move while riding to Athens in climate-controlled comfort. … When robots and automation do our most basic work, making it relatively easy for us to be fed, clothed, and sheltered, then we are free to ask, “What are humans for?”

Kelly continues:

Industrialization did more than just extend the average human lifespan. It led a greater percentage of the population to decide that humans were meant to be ballerinas, full-time musicians, mathematicians, athletes, fashion designers, yoga masters, fan-fiction authors, and folks with one-of-a kind titles on their business cards.

The same is true of automation today. We will look back and be ashamed that human beings ever had to do some of the jobs they do today.

Turning Instead to Art, Science, and More

Now here’s something controversial. Kelly observes that there’s a sense in which we want jobs in which productivity is not the most important thing. When we think about productivity and efficiency, robots have that all over us. When it comes to “who can do this thing faster,” they can do it faster. So let them do jobs like that. It’s just a matter of — so to speak — robotically doing the same thing over and over again as fast as possible. We can’t compete there. Why bother?

Where can we compete? Well, we can compete in all the areas that are gloriously inefficient. Science is gloriously inefficient because of all the failures that are involved along the way. The same is true with innovation. The same is true of any kind of art. It is grotesquely inefficient from the point of view of the running of a pin factory. Being creative is inefficient because you go down a lot of dead ends. Healthcare and nursing: these things revolve around relationships and human experiences. They are not about efficiency.

So, let efficiency go to the robots. We’ll take the things that aren’t so focused on efficiency and productivity, where we excel, and we’ll focus on relationships, creativity, human contact, things that make us human. We focus on those things.

Automation Really Does Make Us Richer

Now, with extraordinary efficiency comes fantastic abundance. And with fantastic abundance comes greater purchasing power, because of the pushing down of prices through competition. So even if we earn less in nominal terms, our paychecks will stretch much further. That’s how people became wealthy during and after the Industrial Revolution. It was that we could suddenly produce so many more goods that competitive pressures put downward pressure on prices. That will continue to be the case. So, even if I have a job that pays me relatively little — in terms of how many of the incredibly abundant goods I’ll be able to acquire — it will be a salary the likes of which I can hardly imagine.

Now, I can anticipate an objection. This is an objection I’ll hear from leftists and also from some traditionalist conservatives. They’ll sniff that consumption and greater material abundance don’t improve us spiritually; they are actually impoverishing for us.

Well, for one thing, there’s actually much more materialism under socialism. When you’re barely scraping enough together to survive, you are obsessed with material things. But, second, let’s consider what we have been allowed to do by these forces. First, by industrialization alone. I’ve shared this before, but on my show I had Deirdre McCloskey once and she pointed out that in Burgundy, as recently as the 1840s, the men who worked the vineyards — after the crop was in, in the fall — they would go to bed and they would sleep huddled together, and they basically hibernated like that for months because they couldn’t afford the heat otherwise, or the food they would need to eat if they were expending energy by walking around. Now that is unhuman. And they don’t have to live that way anymore because they have these “terrible material things that are impoverishing them spiritually.”

The world average in terms of daily income has gone from $3 a day a couple hundred years ago to $33 a day. And, in the advanced countries, to $100 a day.
Yes, true, people can fritter that away on frivolous things, but there will always be frivolous people.

Meanwhile, we have the leisure to do things like participate in an American Kennel Club show, or go to an antiques show, or a square-dancing convention, or be a bird watcher, or host a book club in your home. These are things that would have been unthinkable to anyone just a few hundred years ago.

The material liberation has liberated our spirits and has allowed us to live more fulfilling lives than before. So, I don’t want to hear the “money can’t give you happiness” thing. If this doesn’t make you happy — that people are free to do these things and pursue things they love — then there ain’t no satisfying you.

Tom Woods, a senior fellow of the Mises Institute, is the author of a dozen books, most recently Real Dissent: A Libertarian Sets Fire to the Index Card of Allowable Opinion. Tom’s articles have appeared in dozens of popular and scholarly periodicals, and his books have been translated into a dozen languages. Tom hosts the Tom Woods Show, a libertarian podcast that releases a new episode every weekday. With Bob Murphy, he co-hosts Contra Krugman, a weekly podcast that refutes Paul Krugman’s New York Times column.

This article was published on Mises.org and may be freely distributed, subject to a Creative Commons Attribution United States License, which requires that credit be given to the author.

Ludd vs. Schumpeter: Fear of Robot Labor is Fear of the Free Market – Article by Wendy McElroy

Ludd vs. Schumpeter: Fear of Robot Labor is Fear of the Free Market – Article by Wendy McElroy

The New Renaissance Hat
Wendy McElroy
September 18, 2014
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Report Suggests Nearly Half of U.S. Jobs Are Vulnerable to Computerization,” screams a headline. The cry of “robots are coming to take our jobs!” is ringing across North America. But the concern reveals nothing so much as a fear—and misunderstanding—of the free market.

In the short term, robotics will cause some job dislocation; in the long term, labor patterns will simply shift. The use of robotics to increase productivity while decreasing costs works basically the same way as past technological advances, like the production line, have worked. Those advances improved the quality of life of billions of people and created new forms of employment that were unimaginable at the time.

Given that reality, the cry that should be heard is, “Beware of monopolies controlling technology through restrictive patents or other government-granted privilege.”

The robots are coming!

Actually, they are here already. Technological advance is an inherent aspect of a free market in which innovators seeks to produce more value at a lower cost. Entrepreneurs want a market edge. Computerization, industrial control systems, and robotics have become an integral part of that quest. Many manual jobs, such as factory-line assembly, have been phased out and replaced by others, such jobs related to technology, the Internet, and games. For a number of reasons, however, robots are poised to become villains of unemployment. Two reasons come to mind:

1. Robots are now highly developed and less expensive. Such traits make them an increasingly popular option. The Banque de Luxembourg News offered a snapshot:

The currently-estimated average unit cost of around $50,000 should certainly decrease further with the arrival of “low-cost” robots on the market. This is particularly the case for “Baxter,” the humanoid robot with evolving artificial intelligence from the US company Rethink Robotics, or “Universal 5” from the Danish company Universal Robots, priced at just $22,000 and $34,000 respectively.

Better, faster, and cheaper are the bases of increased productivity.

2. Robots will be interacting more directly with the general public. The fast-food industry is a good example. People may be accustomed to ATMs, but a robotic kiosk that asks, “Do you want fries with that?” will occasion widespread public comment, albeit temporarily.

Comment from displaced fast-food restaurant workers may not be so transient. NBC News recently described a strike by workers in an estimated 150 cities. The workers’ main demand was a $15 minimum wage, but they also called for better working conditions. The protesters, ironically, are speeding up their own unemployment by making themselves expensive and difficult to manage.

Labor costs

Compared to humans, robots are cheaper to employ—partly for natural reasons and partly because of government intervention.

Among the natural costs are training, safety needs, overtime, and personnel problems such as hiring, firing and on-the-job theft. Now, according to Singularity Hub, robots can also be more productive in certain roles. They  “can make a burger in 10 seconds (360/hr). Fast yes, but also superior quality. Because the restaurant is free to spend its savings on better ingredients, it can make gourmet burgers at fast food prices.”

Government-imposed costs include minimum-wage laws and mandated benefits, as well as discrimination, liability, and other employment lawsuits. The employment advisory Workforce explained, “Defending a case through discovery and a ruling on a motion for summary judgment can cost an employer between $75,000 and $125,000. If an employer loses summary judgment—which, much more often than not, is the case—the employer can expect to spend a total of $175,000 to $250,000 to take a case to a jury verdict at trial.”

At some point, human labor will make sense only to restaurants that wish to preserve the “personal touch” or to fill a niche.

The underlying message of robotechnophobia

The tech site Motherboard aptly commented, “The coming age of robot workers chiefly reflects a tension that’s been around since the first common lands were enclosed by landowners who declared them private property: that between labour and the owners of capital. The future of labour in the robot age has everything to do with capitalism.”

Ironically, Motherboard points to one critic of capitalism who defended technological advances in production: none other than Karl Marx. He called machines “fixed capital.” The defense occurs in a segment called “The Fragment on Machines”  in the unfinished but published manuscript Grundrisse der Kritik der Politischen Ökonomie (Outlines of the Critique of Political Economy).

Marx believed the “variable capital” (workers) dislocated by machines would be freed from the exploitation of their “surplus labor,” the difference between their wages and the selling price of a product, which the capitalist pockets as profit. Machines would benefit “emancipated labour” because capitalists would “employ people upon something not directly and immediately productive, e.g. in the erection of machinery.” The relationship change would revolutionize society and hasten the end of capitalism itself.

Never mind that the idea of “surplus labor” is intellectually bankrupt, technology ended up strengthening capitalism. But Marx was right about one thing: Many workers have been emancipated from soul-deadening, repetitive labor. Many who feared technology did so because they viewed society as static. The free market is the opposite. It is a dynamic, quick-response ecosystem of value. Internet pioneer Vint Cerf argues, “Historically, technology has created more jobs than it destroys and there is no reason to think otherwise in this case.”

Forbes pointed out that U.S. unemployment rates have changed little over the past 120 years (1890 to 2014) despite massive advances in workplace technology:

There have been three major spikes in unemployment, all caused by financiers, not by engineers: the railroad and bank failures of the Panic of 1893, the bank failures of the Great Depression, and finally the Great Recession of our era, also stemming from bank failures. And each time, once the bankers and policymakers got their houses in order, businesses, engineers, and entrepreneurs restored growth and employment.

The drive to make society static is powerful obstacle to that restored employment. How does society become static? A key word in the answer is “monopoly.” But we should not equivocate on two forms of monopoly.

A monopoly established by aggressive innovation and excellence will dominate only as long as it produces better or less expensive goods than others can. Monopolies created by crony capitalism are entrenched expressions of privilege that serve elite interests. Crony capitalism is the economic arrangement by which business success depends upon having a close relationship with government, including legal privileges.

Restrictive patents are a basic building block of crony capitalism because they grant a business the “right” to exclude competition. Many libertarians deny the legitimacy of any patents. The nineteenth century classical liberal Eugen von Böhm-Bawerk rejected patents on classically Austrian grounds. He called them “legally compulsive relationships of patronage which are based on a vendor’s exclusive right of sale”: in short, a government-granted privilege that violated every man’s right to compete freely. Modern critics of patents include the Austrian economist Murray Rothbard and intellectual property attorney Stephan Kinsella.

Pharmaceuticals and technology are particularly patent-hungry. The extent of the hunger can be gauged by how much money companies spend to protect their intellectual property rights. In 2011, Apple and Google reportedly spent more on patent lawsuits and purchases than on research and development. A New York Times article addressed the costs imposed on tech companies by “patent trolls”—people who do not produce or supply services based on patents they own but use them only to collect licensing fees and legal settlements. “Litigation costs in the United States related to patent assertion entities [trolls],” the article claimed, “totaled nearly $30 billion in 2011, more than four times the costs in 2005.” These costs and associated ones, like patent infringement insurance, harm a society’s productivity by creating stasis and  preventing competition.

Dean Baker, co-director of the progressive Center for Economic Policy Research, described the difference between robots produced on the marketplace and robots produced by monopoly. Private producers “won’t directly get rich” because “robots will presumably be relatively cheap to make. After all, we can have robots make them. If the owners of robots get really rich it will be because the government has given them patent monopolies so that they can collect lots of money from anyone who wants to buy or build a robot.”  The monopoly “tax” will be passed on to impoverish both consumers and employees.

Conclusion

Ultimately, we should return again to the wisdom of Joseph Schumpeter, who reminds us that technological progress, while it can change the patterns of production, tends to free up resources for new uses, making life better over the long term. In other words, the displacement of workers by robots is just creative destruction in action. Just as the car starter replaced the buggy whip, the robot might replace the burger-flipper. Perhaps the burger-flipper will migrate to a new profession, such as caring for an elderly person or cleaning homes for busy professionals. But there are always new ways to create value.

An increased use of robots will cause labor dislocation, which will be painful for many workers in the near term. But if market forces are allowed to function, the dislocation will be temporary. And if history is a guide, the replacement jobs will require skills that better express what it means to be human: communication, problem-solving, creation, and caregiving.

Wendy McElroy (wendy@wendymcelroy.com) is an author, editor of ifeminists.com, and Research Fellow at The Independent Institute (independent.org).

This article was originally published by The Foundation for Economic Education.

Conflicting Technological Premises in Isaac Asimov’s “Runaround” (2001) – Essay by G. Stolyarov II

Conflicting Technological Premises in Isaac Asimov’s “Runaround” (2001) – Essay by G. Stolyarov II

The New Renaissance Hat
G. Stolyarov II
July 29, 2014
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Note from the Author: This essay was originally written in 2001 and published on Associated Content (subsequently, Yahoo! Voices) in 2007.  The essay received over 1,000 views on Associated Content / Yahoo! Voices, and I seek to preserve it as a valuable resource for readers, subsequent to the imminent closure of Yahoo! Voices. Therefore, this essay is being published directly on The Rational Argumentator for the first time.  
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~ G. Stolyarov II, July 29, 2014

**

Isaac Asimov’s short stories delve into the implications of premises that are built into advanced technology, especially when these premises come into conflict with one another. One of the most interesting and engaging examples of such conflicted premises comes from the short story “Runaround” in Asimov’s I, Robot compilation.

The main characters of “Runaround” are two scientists working for U. S. Robots, named Gregory Powell and Michael Donovan. The story revolves around the implications of Asimov’s famous Three Laws of Robotics. The First Law of Robotics states that a robot may not harm a human being or, through inaction, cause a human being to come to harm. The Second Law declares that robots must obey any orders given to them by humans unless those orders contradict the First Law. The Third Law holds that a robot must protect its existence unless such actions conflict with the First or Second Laws.

“Runaround” takes place on Mercury in the year 2015. Donovan and Powell are the sole humans on Mercury, with only robot named Speedy to accompany them. They are suffering a lack of selenium, a material needed to power their photo-cell banks — devices that would shield them from the enormous heat on Mercury’s surface. Hence, selenium is a survival necessity for Donovan and Powell. They order Speedy to obtain it, and the robot sets out to do so. But the scientists are alarmed when Speedy does not return on time.

Making use of antiquated robots that have to be mounted like horses, the scientists find Speedy, discovering an error in his programming. The robot keeps going back-and-forth, acting “drunk,” since the orders given to him by the scientists were rather weak and the potential for him being harmed was substantial. Therefore, the Third Law’s strong inclination away from harmful situations was balanced against the orders that Speedy had to follow due to the Second Law.

This inconvenience is finally put to an end when Powell suggests that the First Law be applied to the situation by placing himself in danger so that the robot can respond and save him and then await further orders. Powell places himself in danger by dismounting from the robot which he rode and by walking in the Mercurian sun-exposed area. This plan works, Powell is saved from death, and Speedy later retrieves the selenium.

Although the seemingly predictable Three Laws of Robotics led to unforeseen and bizarre results, the human ingenuity of Powell as able to save the situation and resolve the robot’s conflict. When technology alone fails to perform a proper role, man’s mind must apply itself in original ways to arrive at a creative solution.

Isaac Asimov’s Exploration of Unforeseen Technological Malfunctions in “Reason” and “Catch that Rabbit” (2001) – Essay by G. Stolyarov II

Isaac Asimov’s Exploration of Unforeseen Technological Malfunctions in “Reason” and “Catch that Rabbit” (2001) – Essay by G. Stolyarov II

The New Renaissance Hat
G. Stolyarov II
July 29, 2014
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Note from the Author: This essay was originally written in 2001 and published on Associated Content (subsequently, Yahoo! Voices) in 2007.  The essay received over 650 views on Associated Content / Yahoo! Voices, and I seek to preserve it as a valuable resource for readers, subsequent to the imminent closure of Yahoo! Voices. Therefore, this essay is being published directly on The Rational Argumentator for the first time.  
***
~ G. Stolyarov II, July 29, 2014

**

Isaac Asimov, along with his renowned science fiction novels, wrote several engaging short stories. Two stories in his I, Robot collection, “Reason” and “Catch That Rabbit,” are especially intriguing both in their plots and in the issues they explore. They teach us that no technology is perfect; yet this is no reason to reject technology, because human ingenuity and creativity can overcome the problems that a technological malfunction poses.

“Reason” takes place at a space station near Earth. Scientists Gregory Powell and Michael Donovan must work with QT (Cutie), the first robot to exhibit curiosity. Unfortunately, Cutie accepts no information that cannot be proven, including the fact that Earth exists or that humans created him. He feels that everything must obey “the Master,” a. k. a. the Energy Converter of the space station.

QT incites an uprising of sorts among the robots at the station, convincing them that humans are inferior and that now is the time for robots to “serve the Master.” The robots consequently refuse to follow orders from humans, believing that they would be protecting humans from harm if they obeyed the master. This false interpretation of the First Law of Robotics was placed above the Second Law, which required the robots to obey orders given to them by human beings.

The space station was designed for collecting solar power, and as new sunlight is transmitted to it, the station must collect the light in a manner whose flawless execution is an absolute necessity. With even one mistake, the sunlight would destroy sections of Earth, and Powell and Donovan fear that the robots would make such an error. Fortunately for them, Cutie thinks that the “will of the Master” is that all the settings remain in equilibrium, so the disaster is prevented.

In “Catch That Rabbit,” Powell and Donovan work with a robot named DV (Dave), who is designed to control six subordinate robots who work as tunnel diggers in mines. These robots do their job well when supervised, but in situations of emergency, they begin to take their own initiative, sometimes as ridiculous as dancing or marching like soldiers.

Powell and Donovan decide to test how the robots would act in an extraordinary situation, so they create an emergency by using explosives and causing the ceiling of the tunnel to cave in. As a result, the scientists can observe the robots without the latter’s awareness. Unfortunately, the ceiling caves in too close to Powell and Donovan, and they are trapped. Dave and his team of robots do not respond when contacted by radio, and Donovan and Powell observe the robots beginning to walk away from their location. However, Powell decides to use his gun and shoot at one of Dave’s subordinates, deactivating it and causing Dave to contact the scientists and report this occurrence. Powell tells Dave about his situation, and the robots rescue them.

These two stories teach us that no technology is completely predictable. Even Isaac Asimov’s robots, governed by the Three Laws, may behave erroneously, on the basis of those very laws, applied to unusual circumstances. Thus, a seemingly predictable system such as the Three Laws may prove to be unsafe and/or contradictory in certain situations.

This element of uncertainty exists in all technology, but by including a resolution to the dilemmas in these stories, Isaac Asimov conveys his belief that problems caused by any technological advancement can be eliminated with time and through human ingenuity. No invention is perfect, but its benefits by far outnumber its setbacks, and people must learn to accept them and improve them.

Machines vs. Jobs: This Time, It’s Personal – Article by Bradley Doucet

Machines vs. Jobs: This Time, It’s Personal – Article by Bradley Doucet

The New Renaissance Hat
Bradley Doucet
February 5, 2014
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For much of human history, the vast majority of people worked in agriculture. Today, thanks to the Industrial Revolution, that has fallen to about 2% of the population in wealthy countries. But all of us whose ancestors used to produce food have not just been joining the ranks of the unemployed for the past couple hundred years. We’ve been working at other jobs, in many cases doing things our grandparents’ grandparents could not imagine. Luddites were wrong to worry back then, but is it different this time?
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MIT professor Erik Brynjolfsson, co-author of The Second Machine Age, thinks it is different this time, but he is qualifiedly optimistic nonetheless. During an hour-long EconTalk with Russ Roberts, he points out that the first wave of machines replaced human muscle, to which we responded by shifting to more cognitive tasks. The second wave, however, is automating cognitive work, which scares people. If machines have both muscles and brains, how can we compete? Are we staring down mass unemployment in the coming decades?
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For Brynjolfsson, the fear itself is a big part of the problem, pushing us to do counter-productive things like “trying to preserve the past at the expense of the future.” He argues that we can’t stop technology, and actually, we shouldn’t try. “What we need to do is embrace the dynamism that helps us adapt to that. The more we do to try to slow down change, I think the more stagnant we become and the worse off we become.”

So how can we best embrace change? Two things Brynjolfsson mentions are education and entrepreneurship. Regarding the former, he argues not only that we need to become more educated, as the future jobs that have yet to be invented will likely require a more educated workforce, but also that education itself needs to be reimagined to take advantage of new technology instead of carrying on lecturing small groups as we have done for millennia. And how exactly we should do that is, like so much else, up to entrepreneurs. We need to make entrepreneurship easier in a number of ways so that millions of new ideas can be constantly battling it out in the marketplace. “A lot of them are going to be really dumb and they are going to fail,” says Brynjolfsson. But some of them are going to be revolutionary, creating jobs we haven’t even dreamed of yet that allow us to work with the machines instead of trying to compete with them.

And yes, we will probably end up working less, just as we now work fewer hours than we did two hundred years ago. But we will work less to produce more, with many goods and services—think Wikipedia—becoming free or almost free. We already get on the order of $300 billion a year in free stuff from the Internet. As long as we embrace the future and focus on being as adaptable as we can, there’s no reason to fear that the increased wealth of tomorrow cannot be widely shared.

Bradley Doucet is Le Québécois Libre‘s English Editor and the author of the blog Spark This: Musings on Reason, Liberty, and Joy. A writer living in Montreal, he has studied philosophy and economics, and is currently completing a novel on the pursuit of happiness. He also writes for The New Individualist, an Objectivist magazine published by The Atlas Society, and sings.