Tag Archives: Robotics

The Hard Problem of Consciousness is Not That Hard

The Hard Problem of Consciousness is Not That Hard

GUEST POST from Geoffrey A. Moore

We human beings like to believe we are special—and we are, but not as special as we might like to think. One manifestation of our need to be exceptional is the way we privilege our experience of consciousness. This has led to a raft of philosophizing which can be organized around David Chalmers’ formulation of “the hard problem.”

In case this is a new phrase for you, here is some context from our friends at Wikipedia:

“… even when we have explained the performance of all the cognitive and behavioral functions in the vicinity of experience—perceptual discrimination, categorization, internal access, verbal report—there may still remain a further unanswered question: Why is the performance of these functions accompanied by experience?”

— David Chalmers, Facing up to the problem of consciousness

The problem of consciousness, Chalmers argues, is two problems: the easy problems and the hard problem. The easy problems may include how sensory systems work, how such data is processed in the brain, how that data influences behavior or verbal reports, the neural basis of thought and emotion, and so on. The hard problem is the problem of why and how those processes are accompanied by experience.3 It may further include the question of why these processes are accompanied by that particular experience rather than another experience.

The key word here is experience. It emerges out of cognitive processes, but it is not completely reducible to them. For anyone who has read much in the field of complexity, this should not come as a surprise. All complex systems share the phenomenon of higher orders of organization emerging out of lower orders, as seen in the frequently used example of how cells, tissues, organs, and organisms all interrelate. Experience is just the next level.

The notion that explaining experience is a hard problem comes from locating it at the wrong level of emergence. Materialists place it too low—they argue it is reducible to physical phenomena, which is simply another way of denying that emergence is a meaningful construct. Shakespeare is reducible to quantum effects? Good luck with that.

Most people’s problems with explaining experience, on the other hand, is that they place it too high. They want to use their own personal experience as a grounding point. The problem is that our personal experience of consciousness is deeply inflected by our immersion in language, but it is clear that experience precedes language acquisition, as we see in our infants as well as our pets. Philosophers call such experiences qualia, and they attribute all sorts of ineluctable and mysterious qualities to them. But there is a much better way to understand what qualia really are—namely, the pre-linguistic mind’s predecessor to ideas. That is, they are representations of reality that confer strategic advantage to the organism that can host and act upon them.

Experience in this context is the ability to detect, attend to, learn from, and respond to signals from our environment, whether they be externally or internally generated. Experiences are what we remember. That is why they are so important to us.

Now, as language-enabled humans, we verbalize these experiences constantly, which is what leads us to locate them higher up in the order of emergence, after language itself has emerged. Of course, we do have experiences with language directly—lots of them. But we need to acknowledge that our identity as experiencers is not dependent upon, indeed precedes our acquisition of, language capability.

With this framework in mind, let’s revisit some of the formulations of the hard problem to see if we can’t nip them in the bud.

  • The hard problem of consciousness is the problem of explaining why and how we have qualia or phenomenal experiences. Our explanation is that qualia are mental abstractions of phenomenal experiences that, when remembered and acted upon, confer strategic advantage to organisms under conditions of natural and sexual selection. Prior to the emergence of brains, “remembering and acting upon” is a function of chemical signals activating organisms to alter their behavior and, over time, to privilege tendencies that reinforce survival. Once brain emerges, chemical signaling is supplemented by electrical signaling to the same ends. There is no magic here, only a change of medium.
  • Annaka Harris poses the hard problem as the question of “how experience arise[s] out of non-sentient matter.” The answer to this question is, “level by level.” First sentience has to emerge from non-sentience. That happens with the emergence of life at the cellular level. Then sentience has to spread beyond the cell. That happens when chemical signaling enables cellular communication. Then sentience has to speed up to enable mobile life. That happens when electrical signaling enabled by nerves supplements chemical signaling enabled by circulatory systems. Then signaling has to complexify into meta-signaling, the aggregation of signals into qualia, remembered as experiences. Again, no miracles required.
  • Others, such as Daniel Dennett and Patricia Churchland believe that the hard problem is really more of a collection of easy problems, and will be solved through further analysis of the brain and behavior. If so, it will be through the lens of emergence, not through the mechanics of reductive materialism.
  • Consciousness is an ambiguous term. It can be used to mean self-consciousness, awareness, the state of being awake, and so on. Chalmers uses Thomas Nagel’s definition of consciousness: the feeling of what it is like to be something. Consciousness, in this sense, is synonymous with experience. Now we are in the language-inflected zone where we are going to get consciousness wrong because we are entangling it in levels of emergence that come later. Specifically, to experience anything as like anything else is not possible without the intervention of language. That is, likeness is not a qualia, it is a language-enabled idea. Thus, when Thomas Nagel famously asked, “What is it like to be a bat?” he is posing a question that has meaning only for humans, never for bats.

Going back to the first sentence above, self-consciousness is another concept that has been language-inflected in that only human beings have selves. Selves, in other words, are creations of language. More specifically, our selves are characters embedded in narratives, and use both the narratives and the character profiles to organize our lives. This is a completely language-dependent undertaking and thus not available to pets or infants. Our infants are self-sentient, but it is not until the little darlings learn language, hear stories, then hear stories about themselves, that they become conscious of their own selves as separate and distinct from other selves.

On the other hand, if we use the definitions of consciousness as synonymous with awareness or being awake, then we are exactly at the right level because both those capabilities are the symptoms of, and thus synonymous with, the emergence of consciousness.

  • Chalmers argues that experience is more than the sum of its parts. In other words, experience is irreducible. Yes, but let’s not be mysterious here. Experience emerges from the sum of its parts, just like any other layer of reality emergences from its component elements. To say something is irreducible does not mean that it is unexplainable.
  • Wolfgang Fasching argues that the hard problem is not about qualia, but about pure what-it-is-like-ness of experience in Nagel’s sense, about the very givenness of any phenomenal contents itself:

Today there is a strong tendency to simply equate consciousness with qualia. Yet there is clearly something not quite right about this. The “itchiness of itches” and the “hurtfulness of pain” are qualities we are conscious of. So, philosophy of mind tends to treat consciousness as if it consisted simply of the contents of consciousness (the phenomenal qualities), while it really is precisely consciousness of contents, the very givenness of whatever is subjectively given. And therefore, the problem of consciousness does not pertain so much to some alleged “mysterious, nonpublic objects”, i.e. objects that seem to be only “visible” to the respective subject, but rather to the nature of “seeing” itself (and in today’s philosophy of mind astonishingly little is said about the latter).

Once again, we are melding consciousness and language together when, to be accurate, we must continue to keep them separate. In this case, the dangerous phrase is “the nature of seeing.” There is nothing mysterious about seeing in the non-metaphorical sense, but that is not how the word is being used here. Instead, “seeing” is standing for “understanding” or “getting” or “grokking” (if you are nerdy enough to know Robert Heinlein’s Stranger in a Strange Land). Now, I think it is reasonable to assert that animals “grok” if by that we mean that they can reliably respond to environmental signals with strategic behaviors. But anything more than that requires the intervention of language, and that ends up locating consciousness per se at the wrong level of emergence.

OK, that’s enough from me. I don’t think I’ve exhausted the topic, so let me close by saying…

That’s what I think, what do you think?

Image Credit: Pixabay

Subscribe to Human-Centered Change & Innovation WeeklySign up here to join 17,000+ leaders getting Human-Centered Change & Innovation Weekly delivered to their inbox every week.

The Robots Aren’t Really Going to Take Over

The Robots Aren't Really Going to Take Over

GUEST POST from Greg Satell

In 2013, a study at Oxford University found that 47% of jobs in the United States are likely to be replaced by robots over the next two decades. As if that doesn’t seem bad enough, Yuval Noah Harari, in his bestselling book Homo Deus, writes that “humans might become militarily and economically useless.” Yeesh! That doesn’t sound good.

Yet today, ten years after the Oxford Study, we are experiencing a serious labor shortage. Even more puzzling is that the shortage is especially acute in manufacturing, where automation is most pervasive. If robots are truly taking over, then why are having trouble finding enough humans to do work that needs being done?

The truth is that automation doesn’t replace jobs, it replaces tasks and when tasks become automated, they largely become commoditized. So while there are significant causes for concern about automation, such as increasing returns to capital amid decreasing returns to labor, the real danger isn’t with automation itself, but what we choose to do with it.

Organisms Are Not Algorithms

Harari’s rationale for humans becoming useless is his assertion that “organisms are algorithms.” Much like a vending machine is programed to respond to buttons, humans and other animals are programed by genetics and evolution to respond to “sensations, emotions and thoughts.” When those particular buttons are pushed, we respond much like a vending machine does.

He gives various data points for this point of view. For example, he describes psychological experiments in which, by monitoring brainwaves, researchers are able to predict actions, such as whether a person will flip a switch, even before he or she is aware of it. He also points out that certain chemicals, such as Ritalin and Prozac, can modify behavior.

Therefore, he continues, free will is an illusion because we don’t choose our urges. Nobody makes a conscious choice to crave chocolate cake or cigarettes any more than we choose whether to be attracted to someone other than our spouse. Those things are a product of our biological programming.

Yet none of this is at all dispositive. While it is true that we don’t choose our urges, we do choose our actions. We can be aware of our urges and still resist them. In fact, we consider developing the ability to resist urges as an integral part of growing up. Mature adults are supposed to resist things like gluttony, adultery and greed.

Revealing And Building

If you believe that organisms are algorithms, it’s easy to see how humans become subservient to machines. As machine learning techniques combine with massive computing power, machines will be able to predict, with great accuracy, which buttons will lead to what actions. Here again, an incomplete picture leads to a spurious conclusion.

In his 1954 essay, The Question Concerning Technology the German philosopher Martin Heidegger sheds some light on these issues. He described technology as akin to art, in that it reveals truths about the nature of the world, brings them forth and puts them to some specific use. In the process, human nature and its capacity for good and evil is also revealed.

He gives the example of a hydroelectric dam, which reveals the energy of a river and puts it to use making electricity. In much the same sense, Mark Zuckerberg did not “build” a social network at Facebook, but took natural human tendencies and channeled them in a particular way. After all, we go online not for bits or electrons, but to connect with each other.

In another essay, Building Dwelling Thinking, Heidegger explains that building also plays an important role, because to build for the world, we first must understand what it means to live in it. Once we understand that Mark Zuckerberg, or anyone else for that matter, is working to manipulate us, we can work to prevent it. In fact, knowing that someone or something seeks to control us gives us an urge to resist. If we’re all algorithms, that’s part of the code.
Social Skills Will Trump Cognitive Skills

All of this is, of course, somewhat speculative. What is striking, however, is the extent to which the opposite of what Harari and other “experts” predict is happening. Not only have greater automation and more powerful machine learning algorithms not led to mass unemployment it has, as noted above, led to a labor shortage. What gives?

To understand what’s going on, consider the legal industry, which is rapidly being automated. Basic activities like legal discovery are now largely done by algorithms. Services like LegalZoom automate basic filings. There are even artificial intelligence systems that can predict the outcome of a court case better than a human can.

So it shouldn’t be surprising that many experts predict gloomy days ahead for lawyers. By now, you can probably predict the punchline. The number of lawyers in the US has increased by 15% since 2008 and it’s not hard to see why. People don’t hire lawyers for their ability to hire cheap associates to do discovery, file basic documents or even, for the most part, to go to trial. In large part, they want someone they can trust to advise them.

The true shift in the legal industry will be from cognitive to social skills. When much of the cognitive heavy lifting can be done by machines, attorneys who can show empathy and build trust will have an advantage over those who depend on their ability to retain large amounts of information and read through lots of documents.

Value Never Disappears, It Just Shifts To Another Place

In 1900, 30 million people in the United States worked as farmers, but by 1990 that number had fallen to under 3 million even as the population more than tripled. So, in a matter of speaking, 90% of American agriculture workers lost their jobs, mostly due to automation. Yet somehow, the twentieth century was seen as an era of unprecedented prosperity.

You can imagine anyone working in agriculture a hundred years ago would be horrified to find that their jobs would vanish over the next century. If you told them that everything would be okay because they could find work as computer scientists, geneticists or digital marketers, they would probably have thought that you were some kind of a nut.

But consider if you told them that instead of working in the fields all day, they could spend that time in a nice office that was cool and dry because of something called “air conditioning,” and that they would have machines that cook meals without needing wood to be chopped and hauled. To sweeten the pot you could tell them that ”work” would mostly consist largely of talking to other people. They may have imagined it as a paradise.

The truth is that value never disappears, it just shifts to another place. That’s why today we have less farmers, but more food and, for better or worse, more lawyers. It is also why it’s highly unlikely that the robots will take over, because we are not algorithms. We have the power to choose.

— Article courtesy of the Digital Tonto blog
— Image credit: Pixabay

Subscribe to Human-Centered Change & Innovation WeeklySign up here to join 17,000+ leaders getting Human-Centered Change & Innovation Weekly delivered to their inbox every week.

4 Key Aspects of Robots Taking Our Jobs

4 Key Aspects of Robots Taking Our Jobs

GUEST POST from Greg Satell

A 2019 study by the Brookings Institution found that over 61% of jobs will be affected by automation. That comes on the heels of a 2017 report from the McKinsey Global Institute that found that 51% of total working hours and $2.7 trillion dollars in wages are highly susceptible to automation and a 2013 Oxford study that found 47% of jobs will be replaced.

The future looks pretty grim indeed until you start looking at jobs that have already been automated. Fly-by-wire was introduced in 1968, but today we’re facing a massive pilot shortage. The number of bank tellers has doubled since ATMs were introduced. Overall, the US is facing a massive labor shortage.

In fact, although the workforce has doubled since 1970, labor participation rates have risen by more than 10% since then. Everywhere you look, as automation increases, so does the demand for skilled humans. So the challenge ahead isn’t so much finding work for humans, but to prepare humans to do the types of work that will be in demand in the years to come.

1. Automation Doesn’t Replace Jobs, It Replaces Tasks

To understand the disconnect between all the studies that seem to be predicting the elimination of jobs and the increasingly dire labor shortage, it helps to look a little deeper at what those studies are actually measuring. The truth is that they don’t actually look at the rate of jobs being created or lost, but tasks that are being automated. That’s something very different.

To understand why, consider the legal industry, which is rapidly being automated. Basic activities like legal discovery are now largely done by algorithms. Services like LegalZoom automate basic filings. There are even artificial intelligence systems that can predict the outcome of a court case better than a human can.

So, it shouldn’t be surprising that many experts predict gloomy days ahead for lawyers. Yet the number of lawyers in the US has increased by 15% since 2008 and it’s not hard to see why. People don’t hire lawyers for their ability to hire cheap associates to do discovery, file basic documents or even, for the most part, to go to trial. In large part, they want someone they can trust to advise them.

In a similar way we don’t expect bank tellers to process transactions anymore, but to help us with things that we can’t do at an ATM. As the retail sector becomes more automated, demand for e-commerce workers is booming. Go to a highly automated Apple Store and you’ll find far more workers than at a traditional store, but we expect them to do more than just ring us up.

2. When Tasks Become Automated, The Become Commoditized

Let’s think back to what a traditional bank looked like before ATMs or the Internet. In a typical branch, you would see a long row of tellers there to process deposits and withdrawals. Often, especially on Fridays when workers typically got paid, you would expect to see long lines of people waiting to be served.

In those days, tellers needed to process transactions quickly or the people waiting in line would get annoyed. Good service was fast service. If a bank had slow tellers, people would leave and go to one where the lines moved faster. So training tellers to process transactions efficiently was a key competitive trait.

Today, however, nobody waits in line at the bank because processing transactions is highly automated. Our paychecks are usually sent electronically. We can pay bills online and get cash from an ATM. What’s more, these aren’t considered competitive traits, but commodity services. We expect them as a basic requisite of doing business.

In the same way, we don’t expect real estate agents to find us a house or travel agents to book us a flight or find us a hotel room. These are things that we used to happily pay for, but today we expect something more.

3. When Things Become Commodities, Value Shifts Elsewhere

In 1900, 30 million people in the United States were farmers, but by 1990 that number had fallen to under 3 million even as the population more than tripled. So, in a manner of speaking, 90% of American agriculture workers lost their jobs, mostly due to automation. Still, the twentieth century became an era of unprecedented prosperity.

We’re in the midst of a similar transformation today. Just as our ancestors toiled in the fields, many of us today spend much of our time doing rote, routine tasks. However, as two economists from MIT explain in a paper, the jobs of the future are not white collar or blue collar, but those focused on non-routine tasks, especially those that involve other humans.

Consider the case of bookstores. Clearly, by automating the book buying process, Amazon disrupted superstore book retailers like Barnes & Noble and Borders. Borders filed for bankruptcy in 2011 and was liquidated later that same year. Barnes & Noble managed to survive but has been declining for years.

Yet a study at Harvard Business School found that small independent bookstores are thriving by adding value elsewhere, such as providing community events, curating titles and offering personal recommendations to customers. These are things that are hard to do well at a big box retailer and virtually impossible to do online.

4. Value Is Shifting from Cognitive Skills to Social Skills

20 or 30 years ago, the world was very different. High value work generally involved retaining information and manipulating numbers. Perhaps not surprisingly, education and corporate training programs were focused on teaching those skills and people would build their careers on performing well on knowledge and quantitative tasks.

Today, however, an average teenager has more access to information and computing power than a typical large enterprise had a generation ago, so knowledge retention and quantitative ability have largely been automated and devalued. High value work has shifted from cognitive skills to social skills.

Consider that the journal Nature has found that the average scientific paper today has four times as many authors as one did in 1950, and the work they are doing is far more interdisciplinary and done at greater distances than in the past. So even in highly technical areas, the ability to communicate and collaborate effectively is becoming an important skill.

There are some things that a machine will never do. Machines will never strike out at a Little League game, have their hearts broken or see their children born. That makes it difficult, if not impossible, for machines to relate to humans as well as a human can. The future of work is humans collaborating with other humans to design work for machines.

— Article courtesy of the Digital Tonto blog
— Image credit: Pixabay

Subscribe to Human-Centered Change & Innovation WeeklySign up here to get Human-Centered Change & Innovation Weekly delivered to your inbox every week.

Top 10 Human-Centered Change & Innovation Articles of August 2022

Top 10 Human-Centered Change & Innovation Articles of August 2022Drum roll please…

At the beginning of each month we will profile the ten articles from the previous month that generated the most traffic to Human-Centered Change & Innovation. Did your favorite make the cut?

But enough delay, here are August’s ten most popular innovation posts:

  1. Why Amazon Wants to Sell You Robots — by Shep Hyken
  2. Now is the Time to Design Cost Out of Our Products — by Mike Shipulski
  3. How Consensus Kills Innovation — by Greg Satell
  4. The Four Secrets of Innovation Implementation — by Shilpi Kumar
  5. Reset and Reconnect in a Chaotic World — by Janet Sernack
  6. This 9-Box Grid Can Help Grow Your Best Future Talent — by Soren Kaplan
  7. ‘Fail Fast’ is BS. Do This Instead — by Robyn Bolton
  8. The Power of Stopping — by Mike Shipulski
  9. The Battle Against the Half-Life of Learning — by Douglas Ferguson
  10. The Phoenix Checklist – Strategies for Innovation and Regeneration — by Teresa Spangler

BONUS – Here are five more strong articles published in July that continue to resonate with people:

If you’re not familiar with Human-Centered Change & Innovation, we publish 4-7 new articles every week built around innovation and transformation insights from our roster of contributing authors and ad hoc submissions from community members. Get the articles right in your Facebook, Twitter or Linkedin feeds too!

Have something to contribute?

Human-Centered Change & Innovation is open to contributions from any and all innovation and transformation professionals out there (practitioners, professors, researchers, consultants, authors, etc.) who have valuable human-centered change and innovation insights to share with everyone for the greater good. If you’d like to contribute, please contact me.

P.S. Here are our Top 40 Innovation Bloggers lists from the last two years:

Subscribe to Human-Centered Change & Innovation WeeklySign up here to get Human-Centered Change & Innovation Weekly delivered to your inbox every week.

Robots and Automation

Redefining Industries and the Workforce

Robots and Automation

GUEST POST from Art Inteligencia

The world is undergoing a technological revolution, where robots and automation are increasingly prevalent in industries, altering the way we work and transforming entire sectors. This paradigm shift has given rise to a new era for the global workforce, with significant implications for the economy and society as a whole. In this thought leadership article, we will explore how robots and automation redefine industries and reshape the workforce by examining two compelling case study examples.

Case Study 1: The Automotive Industry

The automotive industry has witnessed a remarkable transformation due to the integration of robots and automation. Assembly lines that were once dominated by human labor have now become hubs of robotic efficiency. Manufacturing giants like Tesla and Toyota have turned to automation to enhance production speed, improve quality control, and ultimately increase profitability.

The deployment of robots and automation in the automotive sector has proven to be a game-changer. By automating repetitive and labor-intensive tasks, such as welding, painting, and assembly, manufacturers have achieved greater precision and consistency in their operations. This shift has also led to a reduction in workplace injuries, as robots effectively handle hazardous tasks and operate in environments inhospitable to humans.

Yet, the introduction of automation in the automotive industry has not come without its challenges. While overall productivity has surged, concerns about job displacement have mounted. However, it is important to note that automation has typically resulted in the creation of new jobs that are more cognitively demanding and require advanced technical skills. Moreover, the shift to automation allows human workers to be up-skilled in areas such as robot programming, maintenance, and supervision, leading to higher job satisfaction and improved career prospects.

Case Study 2: E-commerce and Warehousing

The rapid growth of e-commerce has revolutionized the retail industry, prompting a surge in demand for warehousing and fulfillment centers. Robots and automation have played a pivotal role in meeting this demand by redefining the warehousing landscape. Companies like Amazon have embraced robotics to optimize their logistics operations, enhance efficiency, and streamline processes.

Robots deployed in e-commerce warehouses are capable of picking, packing, and sorting products at remarkable speeds, far surpassing the capabilities of human workers. They navigate the warehouse floor with precision and utilize machine learning algorithms to continuously improve their performance. Automation allows for a much quicker order fulfillment process, leading to reduced delivery times and improved customer satisfaction.

While the use of robots in e-commerce warehouses has raised concerns about job displacement, it is vital to understand the broader picture. As demand for online shopping and rapid delivery increases, the need for more sophisticated logistics operations grows as well. This expansion necessitates a larger workforce to manage, program, and maintain the robotic systems. Furthermore, the integration of automation in e-commerce has opened up new opportunities for workers in areas such as inventory management, data analysis, and customer service, illustrating the transformative nature of this technology.

Conclusion

Robots and automation are undoubtedly redefining industries and transforming the global workforce. As exemplified by the automotive industry and e-commerce sector, the integration of this technology has led to increased productivity, improved quality control, and enhanced safety measures. While concerns about job displacement persist, historical evidence suggests that automation creates new roles that require advanced skills, benefiting workers in the long run. To adapt to this rapidly changing landscape, harnessing the potential of robots and automation will be crucial for individuals, companies, and policymakers alike. It is through proactive adaptation and up-skilling that we can embrace this technological revolution and shape a future where robots work alongside humans for the betterment of society.

Bottom line: Futurists are not fortune tellers. They use a formal approach to achieve their outcomes, but a methodology and tools like those in FutureHacking™ can empower anyone to be their own futurist.

Image credit: Wikimedia

Subscribe to Human-Centered Change & Innovation WeeklySign up here to get Human-Centered Change & Innovation Weekly delivered to your inbox every week.

The Future of Robotics: How Automation Will Transform Industries

The Future of Robotics: How Automation Will Transform Industries

GUEST POST from Art Inteligencia

Over the past few decades, advancements in robotics and automation have heralded a new era in industries across the globe. From manufacturing and healthcare to transportation and agriculture, the potential of robots has reached unprecedented heights. This technological revolution has not only increased efficiency and productivity but also sparked considerable speculation about how it will transform various sectors. Two case studies demonstrate the transformative power of automation and provide insights into the future of robotics in industries.

Case Study 1: Automotive Manufacturing

The automotive industry has long been at the forefront of automation, and the rise of robots has significantly transformed the sector. Traditionally, car manufacturing involved human workers on assembly lines performing repetitive tasks. However, the introduction of robots has revolutionized this process, leading to increased precision, speed, and cost-effectiveness.

Tesla, the electric vehicle manufacturer, is a prime example of how robotics have transformed automotive manufacturing. Tesla’s Gigafactory in Nevada, one of the largest manufacturing facilities in the world, heavily relies on automation. The plant is equipped with thousands of robots that perform tasks like welding, painting, and assembly, greatly reducing the need for human labor. As a result, Tesla can produce vehicles faster, with higher quality, and at a lower cost.

The future of robotics in automotive manufacturing lies in the development of autonomous vehicles. Companies like Waymo and Uber are already testing self-driving cars, which will have a profound impact on transportation and mobility. This integration of robotics and artificial intelligence (AI) will not only revolutionize the way vehicles are manufactured but also disrupt the entire automotive industry.

Case Study 2: Healthcare

As the demand for healthcare services continues to rise, robotics and automation offer potential solutions to challenges faced by the sector. From surgical procedures to patient care, robots are being developed to improve medical outcomes, reduce costs, and enhance overall efficiency.

Intuitive Surgical’s da Vinci Surgical System is a prime example of how robotics have transformed surgical procedures. The da Vinci System enables minimally invasive surgeries by providing surgeons with enhanced vision, precision, and control. This advanced robotic technology allows for smaller incisions, reduced blood loss, and faster patient recovery times. As a result, patients experience shorter hospital stays and fewer complications.

In addition to surgical robotics, automation is increasingly being used in rehabilitation and eldercare. Robots like PARO, a therapeutic seal robot, and Pepper, a humanoid social companion robot, are being employed in healthcare settings to provide emotional support, alleviate loneliness, and assist in physical therapy. These robots not only enhance patient experiences but also alleviate the burden on healthcare professionals.

Looking ahead, the future of robotics in the healthcare sector holds immense potential. Advancements in AI and machine learning will enable robots to perform more complex medical procedures, analyze large amounts of patient data, and provide personalized healthcare recommendations.

Conclusion

The future of robotics and automation is undeniably changing the landscape of industries around the world. As seen in the automotive manufacturing and healthcare sectors, robots are revolutionizing traditional processes, increasing efficiency, and improving outcomes. Looking ahead, the integration of AI, machine learning, and advanced robotics will continue to transform industries, leading to increased productivity, cost savings, and even new job opportunities. Harnessing the full potential of robotics and automation will be crucial for industries to thrive in the future.

Bottom line: Futurists are not fortune tellers. They use a formal approach to achieve their outcomes, but a methodology and tools like those in FutureHacking™ can empower anyone to be their own futurist.

Image credit: Pexels

Subscribe to Human-Centered Change & Innovation WeeklySign up here to get Human-Centered Change & Innovation Weekly delivered to your inbox every week.

Robotics and Automation: A Look at the Potential Benefits and Challenges

Robotics and Automation: A Look at the Potential Benefits and Challenges

GUEST POST from Chateau G Pato

Robotics and automation are two technologies that are transforming many industries and causing drastic changes in the way many tasks are completed. While automation certainly has the potential to bring about substantial improvement in efficiency and quality of work, many potential challenges still remain. In this article, we will take a look at the potential benefits and challenges of robotics and automation, as well as discussing two case studies to provide more insight into how the technologies can be utilized.

First, let’s explore some of the beneficial applications of robotics and automation. One of the primary advantages of automation is the potential to reduce costs and streamline processes. By automating tedious and time-consuming tasks, manufacturers can increase production speeds and increase the accuracy of their work. Automated processes can also reduce errors in operations and help businesses remain compliant with relevant regulations. Automation can also reduce worker fatigue and improve worker safety, leading to improved worker satisfaction. In addition, adding robotics to processes is likely to result in much greater output and innovative solutions than manual processes.

Unfortunately, employing robotics and automation can present some challenges. One major challenge is that automation can sometimes require a large upfront investment in terms of purchasing the necessary machinery and integrating the related systems. Additionally, not all processes or tasks are suitable for automation, so companies must choose carefully which processes to automate and which to retain in a manual form. Exploring new technologies can also be difficult and time-consuming for many companies, and robots can require maintenance and repairs while training staff in the new technology.

Now let’s take a look at two case studies that demonstrate robotics and automation in action.

Case Study 1 – Automotive Industry

The first case study comes from the automotive industry, in which companies have implemented robotics and automation into the car production process. Automation has allowed car companies to produce cars much more quickly than before, while maintaining the same or better levels of quality. Automation has also enabled car companies to achieve additional cost savings due to eliminating steps in the production process.

Case Study 1 – Medicine

The second case study comes from the medical field, in which automation has been used to improve accuracy when performing surgeries. Automation has enabled surgeons to be more precise and has also helped reduce errors and complications during surgeries.

Case Study 1 – Conclusion

Robotics and automation can provide significant improvements in efficiency and output when effectively implemented. However, it is important to recognize the potential challenges associated with implementation, such as upfront costs and difficulty in integrating the technology. By taking a closer look at two case studies, we can gain further insight into how robotics and automation can be used in a variety of industries.

Bottom line: Futurology is not fortune telling. Futurists use a scientific approach to create their deliverables, but a methodology and tools like those in FutureHacking™ can empower anyone to engage in futurology themselves.

Image credit: Pexels

Subscribe to Human-Centered Change & Innovation WeeklySign up here to get Human-Centered Change & Innovation Weekly delivered to your inbox every week.

Exploring the Role of AI and Robotics in Futurology

Exploring the Role of AI and Robotics in Futurology

GUEST POST from Art Inteligencia

The field of futurology is constantly evolving and growing in complexity as technology advances. Artificial intelligence (AI) and robotics are two technologies that are playing an increasingly important role in futurology. As we move further into the 21st century, these two fields of technology are being used to create a new era of possibilities and potential. In this article, we will explore the role of AI and robotics in futurology and discuss the ways they are being used to shape the future of our world. Here are five ways AI and robotics will contribute to our future:

1. Smarter and More Efficient Systems

First and foremost, AI and robotics are being used to create smarter and more efficient systems. By using AI and robotics, futurologists are able to create smarter systems that can process more data in a shorter amount of time. This allows for faster decision-making and improved analysis of data. AI and robotics are also being used to create autonomous systems that can make decisions without human input. This allows for faster, more efficient decision-making and improved accuracy.

2. Advanced Methods of Communication

Second, AI and robotics are being used to develop more advanced and sophisticated methods of communication. This includes the development of voice recognition and natural language processing technologies that allow for better communication between humans and machines. AI and robotics are also being used to create more sophisticated forms of communication between humans and machines, such as facial recognition and gesture recognition.

3. Effective and Efficient Goods and Services

Third, AI and robotics are being used to develop more effective and efficient ways of producing goods and services. By using AI and robotics, futurologists are able to create machines that can produce goods faster and more efficiently. This enables companies to reduce production costs and increase their profits. AI and robotics are also being used to create smarter machines that can be used to automate certain tasks, such as packaging and shipping, which increases efficiency and decreases costs.

4. Secure and Reliable Systems

Fourth, AI and robotics are being used to develop more secure and reliable systems. By using AI and robotics, futurologists are able to create systems that are more secure and reliable. This includes systems that are less vulnerable to cyber-attacks and data breaches. AI and robotics are also being used to create systems that can detect threats and respond accordingly.

5. Intelligent and Advanced Transformation

Finally, AI and robotics are being used to develop more intelligent and advanced forms of transportation. This includes the development of self-driving cars and other autonomous vehicles that can navigate roads and other terrain with greater accuracy and safety. AI and robotics are also being used to create smarter forms of transportation that can transport goods and people more efficiently.

Conclusion

AI and robotics are playing an increasingly important role in futurology. By using AI and robotics, futurologists are able to create smarter and more efficient systems, develop more advanced and sophisticated methods of communication, produce goods and services more effectively and efficiently, create more secure and reliable systems, and develop more intelligent and advanced forms of transportation. As technology continues to advance, AI and robotics will continue to play an important role in shaping the future of our world.

Image credit: Pixabay

Subscribe to Human-Centered Change & Innovation WeeklySign up here to get Human-Centered Change & Innovation Weekly delivered to your inbox every week.

Showrooming vs. Retail Warehousing

Showrooming vs. Retail WarehousingOld School vs. Old School

As the saying goes, ‘what’s old is new again’. Only this time robots and hand-held computers (aka smartphones) are involved.

I was having a conversation recently with a colleague about the retail industry and I made the point that all retail stores are warehouses, only some are prettier than others.

Walk into the average Macy’s or other department store and you’ll see piles of inventory out on display in the store, of every size (from small to XXXL) and variety (white, black, brown, etc.) with even more in the back. Retail WarehousingAll of this inventory has been tagged for individual sale and is there every day, just in case the person who wants that size, color, style, whatever, walks into the store ready to take it home today.

Contrast this with Argos in the UK or the now-defunct Best and Service Merchandise in the United States whose business model was to have only certain items out on display in the retail store, with the rest of the inventory in the back ready to be picked (much like an eCommerce environment) once the product(s) were ordered.

Showrooming and Retail Warehousing HybridApple Stores are a hybrid between the two. Accessories are out on the floor boxed for individual sale, while iMac and iBook computers, iPad tablets, and iPod mp3 players are all out of the box and display in droves for customers to try out and hopefully purchase. Then if they do, the box appears from the warehouse in the back.

But there is a new wave of entrepreneurs trying to bring back the catalog retailing business model into the modern age. Version 1 was standard eCommerce where the catalog was available online instead of in the store and no physical retail stores had to be maintained, leading to a financial advantage for online retailers like Amazon. But eCommerce has a weakness, and that is in product categories need to know how something fits or feels or otherwise fits their style or life.

ShowroomingThis has led to the rise of what physical retailers rail against, the concept of showrooming. If you’re not familiar with what showrooming is, it is the pattern of behavior where potential customers come into a physical retail store, explore the product, try it on if necessary, and then leave the store and buy the product online from a competitor like Amazon.

Some entrepreneurs are beginning to recognize the collision of some of the mobile technologies that underlie the showrooming trend together with automated robotic picking technologies and the recognition of inefficiencies in the traditional retail warehousing model.

Hointer Founder

One example is a Seattle area entrepreneur who left Amazon to launch a business called Hointer that while they are talking about how they are revolutionizing the premium jean shopping experience for men, their real strategy is to use their store as a rapid prototyping and testing environment to develop a technology platform supporting the browsing, trying, and checkout process that they hope to sell to a number of different retailers all around the world. Their modernization of the catalog showroom business model is predicated on reducing the square footage and personnel required to operate a store, thus increasing (hopefully) the dollars per square foot ratio that most retailers use as their success metric. One side benefit of the approach is that salespeople will be able to spend less time folding clothes and more time helping customers. Imagine that.

Will this robotic retailing concept catch on with more than utilitarian shoppers?

Image Credits: Daily UW, Hointer


Build a common language of innovation on your team

Subscribe to Human-Centered Change & Innovation WeeklySign up here to get Human-Centered Change & Innovation Weekly delivered to your inbox every week.