Nowadays, smart teapots, intelligent homes and other hi-end devices are making our life easier and better. But what if I tell you, that there is another side. The Internet of Things can change the world, but it can also steal your job.
People are forgetting one small thing, the cost of education. We in a web 3.0 age feel burdened by debt from educations that seemingly try to prepare us for a web/industry 4.0 world but we can't even barely get industry 3.0 jobs. Markets are saturated. Look at pharmacists for example they get into work after schooling to find they will be unemployed because of industries doing vertical and horizontal acquisitions. A blue color worker has no skill set other than doing physical trade labor work. A white collar worker who is in the age bracket of 40s and higher can not simply go back to school to learn industry 4.0 because there is a learning curve. But younger white collar can not get hired into the industry without experience (moving up the latter).
Industry 4.0 will be much more about oportunities than loses. See the kids today, they are not " dolls" anymore , they don' like to be stuck into a classroom with a white board, desks and chairs... They urge for more, and that's why I think, the whole world is changing againg, (a cicle always start and finish at some point, as we see thru history) it's to adap to the new humans that are getting prepared for this insdustry 4.0 or the internet of things!! Thanks for the video, it was super!!!
I love this! Great video! Have you done a 2020 on web 4.0 and industry 4.0? I think this also directly applies to leadership and changes the way we of course work .... but therefore LEAD. Would love to discuss with anyone interested in this topic of the future and the changes and innovations it then demands of leaders....
I dont think that Industry 4.0 will take jobs away. These technologies are majorly assistive and collabrative. But in a market with new technology evolving and the pace of change increasing, it is crucial to consider the business needs for the future and upskill likewise to stay in the game. And this applies not just to those who are freshers but also to those who are already working in organizations.
Embrace automation. Job lose means we can use our time better spent with family and friends or do the things we love. Ubi will be the answer to our job lose problem. #yang2020
A nice informative video and an eye opener for me personally. I believe the world of tomorrow is going to be about how machines and humans can synergise and work together to achieve larger goals. It requires a great vision to look ahead and embrace the upcoming changes that technology is going to bring into the human world. The upcoming human generations would experience a world that is so different from how we experience life today. Of course, this will not happen overnight and would take a few years to reach there gradually, but I don't see this day to be in a distinct future too far away either !
hum...so if so many people lost their jobs,who will consume or pay for tje services? i guess many people forget that capitalism needs a consumer market,so problabily the business guys will think in a way, Besides no one is thinking about the energy that will be necessary to keep it all and the magnetism we will receive....
Plz try to make your video in the form of some written contents.....so we can note it easily....for the making of some kinds of assignments.....like its really difficult to listen every word of a video than to right it.
2025-2050 Unemployment is soaring The second quarter of the 21st century is marked by a rapid rise in unemployment around much of the world.* This results in considerable economic, political and cultural upheaval. For most of the 200 years since the Industrial Revolution, new advances in technology and automation had tended to create more jobs than they destroyed. By the 21st century, however, this was no longer true. A fundamental change had begun to occur.** Median wages, already falling in recent decades, had continued to stagnate - particularly in the West.*** Globalisation and the outsourcing of jobs to overseas markets with lower international labour rates had, of course, been partly responsible in the past. But a growing and rapidly accelerating trend was the impact of machines and intelligent software programs. Not only were their physical abilities becoming more humanlike;******** in many ways their analytical and cognitive skills were beginning to match those of people too.****** Blue collar workers had traditionally borne the brunt of layoffs from technological unemployment. This time, white collar jobs were no longer safe either.* Advanced robotics, increasingly sophisticated algorithms, deep learning networks, exponential growth in computer processing power and bandwidth, voice/facial recognition and other tech - all were paving the way towards a highly automated society. Furthermore, of the (few) new jobs being created, most were in highly skilled roles, making it hard or impossible for those made redundant to adapt. Many workers now faced permanent unemployment. By 2025, transport was among the sectors feeling the biggest impacts.* The idea of self-driving vehicles had once been science fiction, but money was being poured into research and development. In 2015, the first licenced autonomous truck was announced. These hi-tech vehicles saw rapid adoption. Initially they required a driver to be present, who could take over in case of emergencies, but later versions were fully autonomous.* In the US alone, there were 3.5 million truck drivers, with a further 5.2 million people in non-driving jobs that were dependent on the truck-driving industry, such as highway cafes and motels where drivers would stop to eat, drink, rest and sleep. A similar trend would follow with other vehicle types,* such as taxis, alongside public transport including trains - notably the London Underground.* With humans totalling 1/3rd of operating costs from their salaries alone, the business case was strong. Self-driving vehicles would never require a salary, training, sleep, pension payments, health insurance, holidays or other associated costs/time, would never drink alcohol, and never be distracted by mobile phones or tempted by road rage. Manufacturing was another area seeing rapid change. This sector had already witnessed heavy automation in earlier decades, in the form of robots capable of constructing cars. In general, however, these machines were limited to a fixed set of pre-defined movements - repetitive actions performed over and over again. Robots with far more adaptability and dynamism would emerge during the early 21st century. Just one example was "Baxter", developed by Rethink Robotics.* Baxter could understand its environment and was safe enough to work shoulder-to-shoulder with people while offering a broad range of skills. Priced at only $22,000 this model was aimed at midsize and small manufacturers, companies that had never been able to afford robots before. It was fast and easy to configure, going from delivery to the factory floor in under an hour, unlike traditional robots that required manufacturers to develop custom software and make additional capital investments. Robots were increasingly used in aerospace,* agriculture,*** cleaning,* delivery services (via drone),** elderly care homes, hospitals,* hotels,** kitchens,** military operations,**** mining,* retail environments,* security patrols** and warehouses.* In the scientific arena, some machines were now performing the equivalent of 12 years' worth of human research in a week.* Rapid growth in solar PV installations led some analysts to believe that a new era of green jobs was about to explode,* but robots were capable of this task with greater speed and efficiency than human engineers.* Holographic representations of people were also being deployed in various public assistant/receptionist roles. While the first generation lacked the ability to hold a two-way conversation, later versions became more interactive and intelligent.** Other examples of automation included self-service checkouts,* later followed by more advanced forms of "instant" payment via a combination of RFID tracking and doorway scanners* (which also enabled stock levels to be monitored and audited without humans). Cafes and restaurants had begun using a system of touchscreen displays, tablets and mobile apps to improve the speed and accuracy of the order process,* with many establishments also providing machines to rapidly create and dispense meals/drinks,* particularly in fast food chains like McDonalds. AI software, algorithms and mobile apps had exploded in use during the 2010s and this trend continued in subsequent decades. Some bots were now capable of writing and publishing their own articles online.* Virtual lawyers were being developed to predict the likely outcome and impact of law suits; there were virtual doctors and medical bots (such as Watson), with increasingly computerised analysis and reporting of big data (able to find the proverbial "needle in a haystack" with hyper-accuracy and speed);* virtual teachers and other virtual professions. 3D printing was another emerging trend, which by the 2020s had become a mainstream consumer phenomenon for the home* and was increasingly used in large-scale formats and industrial settings too; even for the construction of buildings and vehicles. By 2040, traditional manufacturing jobs had been largely eliminated in the US* and many other Western societies. Meanwhile, the ability to quickly and cheaply print shoes, clothing and other personal items was impacting large numbers of jobs in developing nations, particularly those in Asian sweatshops.* The tide of change was undeniable. All of these developments led to a growing unemployment crisis; not immediately and not everywhere, but enough to become a major issue for society. Unions in the past had attempted to protect their workers from such impacts, but memberships were at record lows - and in any case, they had never been particularly effective in slowing the march of technology and economics. future unemployment trends 2025 2050 timeline Sources: World Bank* and the Oxford Martin Programme on the Impacts of Future Technology* Governments were now facing profound questions about the nature and future direction of their economies. If more and more people were being made permanently unemployed, how could they afford to buy goods and services needed to stimulate growth? Where would tax revenues come from? Confronted by increasingly angry and desperate voters, now protesting on scales dwarfing Occupy Wall Street, many leaders between 2025 and 2050 began formulating a welfare system to handle these extraordinary circumstances. This had gone by several names in the past - such as basic income, basic income guarantee, universal basic income, universal demogrant and citizen's income - but was most commonly referred to as the unconditional basic income (UBI). The concept of UBI was not new. A minimum income for the poor had been discussed as far back as the early 16th century; unconditional grants were proposed in the 18th century; the two were combined for the first time in the 19th century to form the idea of unconditional basic income.* This theory received further attention during the 20th century. The economist Milton Friedman in 1962 advocated a guaranteed income via a "negative income tax". Martin Luther King Jr. in his final book, Where Do We Go from Here: Chaos or Community?, wrote: "I am now convinced that the simplest approach will prove to be the most effective - the solution to poverty is to abolish it directly by a now widely discussed measure: guaranteed income." US President Richard Nixon supported the idea and tried (unsuccessfully) to pass a version of Friedman's plan. His opponent in the 1972 election, George McGovern, also suggested a guaranteed annual income. Traditional welfare payments, such as housing benefit and jobseeker's allowance, were heavily means-tested. In general, they provided only the bare minimum for survival and well-being of a household. By contrast, UBI would be more generous. Unconditional and automatic, it could be paid to each and every individual, regardless of other income sources and with no requirement for a person to work or even be looking for work. The amount paid would make a citizen "economically active", rather than idle, in turn stimulating growth. Some would use the UBI to return to education and improve their skills. Those with jobs would continue to earn more than those who did not work. In most countries, UBI would be funded, in part, by increased taxation on the very rich.* At first glance, this appeared to be a radical left-wing concept involving massive wealth redistribution. For this reason, opposition was initially strong, particularly in the US. As time went by, however, the arguments in favour began to make sense to both sides of the political spectrum. For example, UBI could also be funded by cutting dozens of entitlement programs and replacing them with a single unified solution, reducing the size of government and giving citizens more freedom over their personal finances. Demographics in the US were also shifting in ways that made it very difficult for Republicans
Perfect analysis,but WASP lobby is also fighting back 2020-2024 next term of trump will be eventful.2024 presidential election will decide the fate of this damn world
what makes the world turns? the people but with I4.0 people will be jobless hence know the priority ---- don't be weak read.... think harder my comments are [sufficiently] short .... out of respect for any of you readers true ability ----
We had a talk in my lecture the other day about industry 4.0 it sounds super interesting but there for sure will be a lot less manufacturing jobs. I'm in my final year of university, biomedical manufacturing engineering is what I study. My final year project alone is going to replace 2 people's jobs at least with a machine that I'm designing. I feel horrible doing it knowing how it's going the lives of the operators but oh well, time for me to make some money lol
the idea behind the internet at all is that a decentralized network is less susceptible to overall failure from an error in one computer, since other nodes in the network can take over.
