Tag Archives: artificial intelligence

Education- 4IR Summary

The world is on the precipice of another revolution. New technologies have allowed the human race to push for a new standard of living. In the new future we can help create a world with less poverty, where people can live longer, transform they way we consume energy so it is more efficient, and automate the workforce. These new advancements will drastically change the way we live, and after taking DT&L it has become apparent that the world is not ready for these new technologies. We are progressing so fast when it comes to technology that our society cannot catch up.This is why we have had such massive hacks on our public and private institutions. Us being behind explains why some scientists and inventors are worried with what we will do with AI. Our societal awareness is so far behind our technological awareness that disaster may be looming around the corner and we can not see it. Now how do we fix these problems? The consensus of our class is that education is the key to understanding this new future. The major issue we face, however is that the way our current educational system works is inadequate to help students prepare for this future.

Our current educational system is outdated, even by today’s standards and as the fourth industrial revolution begins our schooling system will be placed further behind than ever before. If students are unprepared for today’s economy then there is little hope schooling will prepare students for the future economy. As our economy is led into another technological revolution it is time for us to take schooling along with it. Yet, how do we do this?

The future of our education system has been a hotly debated issue in politics for decades. Programs like President George Bush’s No Child Left Behind are a recent reminder. Most people agree that there are massive flaws in the way we educate the nation’s youth. The video below went viral last year and has garnered millions of views.

 

 

There have also been many TED talks highlighting the importance of education reform and that the current way of teaching is inadequate. Below is a TED talk from Sir Ken Robinson talking about how to escape education’s death valley.

 

Both of these videos highlight two important flaws that our education system has: It is a rigid system and it stifles individuality. Since there are millions of students in America it was seen as an easier solution to standardize the basics. Standardized tests decided where kids can go to school, which states receive grants, and hammer in basic study skills to students. This system has in turn stifled individuality and this is an issue because it handicaps students who think differently, a perfect analogy is teaching a goldfish to climb a tree. This standardization and mechanization of our education system has held it back from change. Sir Ken Robinson create a good point in his TED Talk, “Education is not a mechanical system it’s a human system.” The main issue plaguing education is that it has failed to adapt to the individual needs of the student and has forced students into a box. Thankfully with the new technologies ushered in by the Fourth Industrial Revolution we have the potential to individualize education and make it possible for every student to learn at their own pace, so everyone can prepare themselves for the future.

 

AI will change the way students from all age groups will learn. The current education system has been in place for over one hundred years and the same static classroom look has not changed. Artificial Intelligence will change the general approach to education to a more focused and refined version for each student. AI will be able to detect what subjects are harder for students at an earlier age and will be able to work with that student to improve his/her skills. The more individualized the education is, the more likely the student will gain more out of the class. Education with the help of AI will become more immersive and will become a long term approach to generating new skills for students. Giving students exposure to smart boards and new online tools such as Slack, will empower them to learn and become more efficient. Artificial intelligence is one the most important technologies in the contemporary world, it is apart of everyone’s daily lives and we are bounded to the power it gives us. The classic student and teacher relationship will become more engaging and less hierarchical. Virtual reality and AI will go hand in hand to create a new way of learning. The ability to learn anytime and anywhere will change the way we view schools and rigid structure.  

 

There is another question we have to ask ourselves when we update our education system What do we want to get out of it? When we are able to create an education system that adapts new technologies and embraces a student’s individuality the question becomes what will we teach. The video below gives a quick explanation on what the new curriculum should be.

 

Near the end of this video an interesting point was made. Education should not end at a certain point, people can continue to grow and learn even after they are no longer in school. With the help of the internet and sites such as Udemy, people can learn new skills at a cheap price. With this new technology and system, adults can learn and experience new things just as students do. This is the future of education and this will help fix the issues like rigidity and lack of individuality. The internet is excellent at passing on information fast and creating new content in response to changing times. With online classes and YouTube teaching channels students can learn what they want to learn and in depth. All of human knowledge and history is available for humans to view. When a new disruptive technology enters the world economy, people will be able to go to the internet and learn how to adapt. In the future someone can learn new skills that will allow them to succeed in an ever changing economy.

The fourth industrial revolution is coming and it is going to completely change the way we see the world. Currently we are unprepared for this revolution. In order to become prepared we have to look at our current education system and fix the flaws plaguing it. We have to make education more personal and fitting for every student and make the system less rigid. Today we have the technology and equipment to implement this properly. In the future we can have an economy that will produce disruptive technologies, but we do not have to fear it. Using the internet we can have people constantly learning new things and adapting themselves to the changing world around them. As talked about in the last POV by some students, we have to keep ourselves up to date. We believe that this dream can be a possibility and that we can update education to fit the challenges of the future and a 21st century world.

So the Climate Is Changing…Now What?

The impact we have on the environment is not something we can overlook, but it is something we have chosen to ignore. If we are trying to look at the big picture of what climate change is and how it is affecting us, the most obvious thing to point out is global warming. While our group did discuss global warming, we decided to focus more on the smaller aspects of climate change and investigated how global warming affected other aspects of the environment. The clear impact of global warming is the rising temperatures, and we discussed the implications of the warmer weather in many different cities. Through investigation, we also stumbled across the impact our pollution has on animals, how it can stir up dormant diseases, or how it can damage our atmosphere. The real focus of our project, however, was the many ways we can mitigate the effects of climate change.

To generalize the numerous problems that are attached to climate change, it is not untrue to say “the end is near and society is essentially screwed.” Climate change is more than the planet getting a “little” hotter. A difference of a few degrees from the average range of the Earth’s temperature has greatly affected the weather, which in turn effects land, and ultimately where life is sustainable. Climate change has caused a domino effect of problems that is perpetuated by continued creation carbon emissions, as well as lack of addressing carbon emissions already present in the atmosphere. Moreover, there is no single solution to fix climate change. Carbon emission may arguably be what facilitate current and future climate change issues, but cutting back on carbon emissions will do virtually nothing to address the issue. Humans have been pumping carbon into the atmosphere for centuries and carbon takes thousands of year to dissipate. As a result, action, like that set by the Paris Accord, will not do much to solve climate change. Even if emissions were cut to zero, the emissions already created would continue to linger, thus perpetuate the effects of climate change. Instead of searching for a single solution to climate change, we need to address every issue individually before they arise.

One effect of global warming is the rise in sea level. Only concerning sea level rising, the increasing temperature of the Earth causes thermal expansion, melting of the ice caps, and ice loss in areas like Greenland and West Antarctica. Thermal expansion and the melting of the polar and glacial ice caps are direct results of global warming; however, unlike the melting ice caps, thermal expansion is reversible if carbon emissions were severally cut back. The melting ice caps are adding more water into the ocean and there is impossible to take that water back. Similarly, ice loss in Greenland and West Antarctica also means more water is flowing into the ocean. Compounding the issue of more water being added into the ocean and the “expansion” of water, the sea level is rising at an alarming rate.

Moreover, if the ice caps are melting then the ocean must be heating up to some extent. Heating of the ocean affects the weather, namely referring to the progression of tropical storms into hurricanes. Hurricanes form in warmer bodies of water. As areas of water heat up, water vapor rises into the air creating thunderstorms. Wind currents then begin to “push” around the storm, thus giving the storm more energy. At 39 mph winds, the thunderstorm is officially a tropical storm, when wind speeds exceed 75 mph the storm is a deemed a hurricane. It is important to understand how hurricanes form because as the ocean heats up, the rising temperature gives these storms more energy, thus become more dangerous. Climate change may not cause more hurricanes, but it may cause more dangerous hurricanes, such as category 4 and 5 hurricanes, to form more frequently. For example, four of the five costliest hurricanes to hit the U.S. have occurred since 2005; these hurricanes include Hurricane Harvey, Hurricane Irma, Hurricane Sandy, and Hurricane Katrina. Hurricane Maria, while it did not hit the U.S., was so strong a new category of hurricanes may be needed to classify it. If more category 4, 5, and possibly 6 hurricanes form, then there could be more damage to coastal areas, infrastructure, and may put more people in danger. For example, Hurricane Maria, arguably a category 6 hurricane, has decimated the electrical grid in Puerto Rico; Puerto Rico may go months without power. It is somewhat bothersome to not have power to watch the news, but to not have power for hospitals is devastating.

The issues of rising sea level and stronger hurricanes combine to make flooding worse and more frequent. As sea level rises, water will consume more land. In addition, if there is an increase in more powerful storms that carry more water and energy, they will leave behind more water further inland. Damage of flooding becomes worse when the infrastructure meant to drain the water overflows, like in Florida. For example, the flooding caused by Hurricane Harvey may take months to recede fully- thus having the potential to destroy whole communities. Moreover, the event of the flood receding may cause additional damage. For example, in Puerto Rico after some of the flood receded, it eroded chunks of land beneath houses. Flooding also perpetuates issues of fixing power lines and transportation.

The following is an image of a house after flooding caused by Hurricane Maria receded:

While there is no universal solution to issues of rising sea level, hurricanes, and flooding, potential solutions do have the characteristic of flexibility in common. For example, past and present solutions to hurricanes and rising sea level are mainly hard defenses. Hard defense are generally man made constructs, such as bulkheads, coastal barrages, and rock walls, used to as a “shield” to stop storms. However, such defenses erode over time, and there is no way of knowing if they will work until the storm arrives. Therefore once it is apparent a hard defense has failed, it is too late to take additional protective measures. On the other hand, soft defenses, such as marshes, and coral reefs, absorb the energy of storms, and move with storms and rising sea level. In addition, soft defenses grow over time and protect against land erosion. For example, marshes have protected the northern coastline of Florida for years. The downsides of soft defenses include the amount of time they take to grow and their inability to be effective on a large scale; marshes would have to extend mile off the coastline of NYC to be effective. However, instead of relying on only hard defenses or only soft defenses, an optimal solution is to use both together. Relying on one or the other is repeating the same mistake of waiting until existing defenses fail and not being able to take additional protective measures. Moreover, we cannot only rely on hard defenses and soft defenses to stop invading sea level and hurricanes because the issue of flooding if they were to fail still holds true. Like hard defenses, there are fixed systems to help mitigate flooding. For example, Tokyo, Japan has a massive canal system that diverts water from Tokyo called the G-Cans Project. The G-Cans Project is a series of underground tunnels that total 3.7 miles long, and vertical shafts that measure 580 feet long, 59 feet high, and 256 feet wide. This network is capable of channeling 12,500,000 L of water per minute. However, for cities like New York City where a major portion of underground real estate is used up, the scale of the G-Cans Project may not be possible. Nevertheless, the format of the system may still be useful because, similar to soft defenses, there is infrastructure that moves with flooding. For example, the POP-UP parking garage moves up and down with water from sewers, thus combing a parking garage and water reservoir. The technology used in the POP-UP garage can also be applied to other architecture that follows the Archimedes Principle. For example, vertical farms, extensive “tower” farms that raises and grows various foods in a controlled environment, using this technology would also be able to move with floods, thus protecting our food sources. However, “POP-UP technology” is still fixed to some extent. Carrying the ideas of flexibility further, Floating City App created floating schools using refurbished shipping containers. These floating schools are solar powered, and include a classroom, a kitchen, and a bathroom. On the other end of the floating infrastructure spectrum, even floating airports have been created. In 2000, Mega Float created a floating airport in Tokyo Bay, Japan that measured 1000 meters long. The airport was so long that it rode multiple wave cycles at once that canceled each other out, and allowed the airport to remain stable. Since the airport was not viewed as necessary, it was dismantled in 2003. However, floating airports are not the limit of floating infrastructure- whole cities could be manufactured to float. Floating cities have the potential to solve the issue of rising sea level and flooding because there would no longer be a worry of losing land, the land would move with the storm.

The following describes the possibility of floating cities:

Stepping back from issues of rising sea level, hurricanes, and flooding, the cause of them is the increase in the temperature, which, alone, is also a threat. By 2100, the Persian Gulf could experience temperatures exceeding 170 degrees Fahrenheit causing the area to become uninhabitable. Areas within the Persian Gulf, such as Doha, Abu Dhabi, and Bander Abbas, some of the richest cities in the world, would have to be abandoned. By 2100, 3 out of 4 people could face deadly heatwaves. Rising temperature will be especially prevalent in cities as a result of the urban heating affect. The urban heating effect states that because of the large amount of human activity within in cities, cities become hotter than the surrounding rural areas. Moreover, the pavement used in cities and human activity does not allow urban areas to properly release the heat absorbed throughout the day at night, thus retaining a high temperature. Immediate solutions to impending dangerous heatwaves include green areas and cooling pavement, in addition to currently implemented cooling centers. Cooling centers are public areas, such as a public library, that offer A/C to the public; however, cooling centers only cool the one building and not necessarily a part of the city. Green areas, by using foliage, create more shade, and thus mitigate pavement heat absorption and lower the overall temperature of an area. An extreme version of green areas are forest cities. Forest cities make plant life an integral part of architecture by covering whole buildings in foliage. By implementing a “jungle,” cities are able to combat the urban heating effect. However, heatwaves are not a problem limited to urban areas. Rural areas, specifically farms, will have to deal with drought because of rising temperatures. In 2012 farmers in the West and Midwest, because of a drought, lost billions of dollars in crops. Additionally, as temperatures increase, vital amounts of food may be lost. If water becomes constrained, it will need to be used efficiently; “spongy” soil is a potential solution. “Spongy” soil retains more water and reduces run off, and therefore gets the most use out of water during drought and collects water during storms. The soil could also be used to cultivate the green areas in the urban areas discussed earlier. Moreover, the soil would complement the use of vertical farms by optimizing the use of water. The rise of global temperature will affect the entire world. People can move to escape rising sea level and floods, but there is no “escaping” rising temperature.

We examined the impact of rising temperatures in developed cities, but they also have an effect on animals in areas without a large human populace and our National Parks. The animals rely on the resources their environment is able to provide them. However, with the increased ocean temperatures and the melting of the ice caps, their ecosystems are being severely disrupted. For example, marine animals, like penguins, in the northern hemisphere are attuned to arctic temperatures and an abundance of krill in the water. The krill are also accustomed to the colder water, but when the temperature of the water rises, they elect to move to where there is cold water. The penguins in that region with a krill-based diet now need to alter their diet to something else. There are many dangers like the lack of nutrients in other shellfish or the potential risk of it being poisonous or otherwise detrimental to their health. Animals are innocent bystanders in our path to destroying the natural resources and we need to take the necessary measures to cut our impact in their environments. One way, albeit extreme, is to adopt a vegan lifestyle. It has many environmental benefits and cuts back on the suffering animals face. We can also take larger steps to cut back on emissions that are a leading factor of the temperature rise. The rise in temperature is also affects Glacier National Park, for the reasons stated in the paragraph above. Another park that is being affected is Grand Canyon National Park. The Colorado River flows through the whole park, but over the years, it is clear to see the decline of the water level. Some of this is due to the erosion, but a majority is the rising temperature causing evaporation. The water is disappearing before our eyes and we are turning a blind eye. What will happen when the water dries up and the ecosystems throughout the canyon are left to scramble for a new water source? We need to take action before we lose these national treasures.

The rise in temperature is also causing something that seems straight out of a sci-fi post-apocalyptic movie- zombie diseases. These are diseases that have been hidden in ice for years, encased in permafrost. We are not equipped or ready to deal with anthrax, small pox, or even a variation of the plague. It is not all that surprising that miners want to push aside the dangers of these diseases to access mineral and petroleum deposits. However, we need to acknowledge the dangers these diseases present and how they could affect our world. A recent outbreak of anthrax in Serbia illustrated the peril of allowing this issue to go unsolved. Many died because a deer encapsulated in ice thawed and, with it, a strain of anthrax. It contaminated the soil and the water, which led to poisoned crops. We also face the issue of refugees carrying local diseases, like dengue fever or malaria, into other countries where citizens’ immune systems are not accustomed to these new diseases. The warmer temperatures are the force behind some refugees leaving their homes, but it can also allow the diseases like Lyme disease and rat lungworm to survive in places they never could before. Therefore, any disease that can thrive in warmer temperature may soon have increased outbreaks- not just the ones already listed. If multiple outbreaks occurred at the same time, we would not be equipped to handle the aftermath.

Global warming is not the only causation we face. Another driving motion of climate change is pollution. While it is expected that we discuss the pollution of the ocean or streets, those types of pollutions are not destroying our atmosphere- space junk is. Space junk refers to the remains of objects that have entered space, and became trapped in the Earth’s atmosphere.

Because of the increasing temperature in the lower atmosphere, the temperature of the upper atmosphere decreases, causing a contraction of that layer. When the atmosphere contracts, air is removed and less friction is in the upper atmosphere. Therefore, the space junk would not be able to re-enter the atmosphere and burn up, so they remain on the outer layer of our atmosphere. If this junk remains in the atmosphere, it can hit other satellites and create more debris, which can then hit another satellite and make more debris and so on. There is no long-term solution for the dealing with space junk, but there is a satellite created by CleanSpace One that can grab debris and bring it back down to Earth, so it can burn upon re-entry. The downside to using this satellite is that the satellite can only be used once, as it burns upon re-entry as well. Another, more lasting solution, would be the use of materials that break apart gradually after they are exposed to ultra-violet rays. Other satellites that are helping us combat climate change are cube satellites. These satellites were created to scan the Earth’s surface and collect data about which areas are more prone to hurricanes, how hurricanes form, and they are significantly cheaper than normal satellites. These satellites have a shorter shelf-life, which means we will have to replace them more often. However, that also means we can update the software regularly and modify design whenever necessary. If we used the data from these satellites to fuel a flood-predicting AI, it would be able to learn better with the extra information. Other types of AI can also be used to discover new and more efficient ways to combat climate change.

We are currently in an administration that refuses to acknowledge or believe in the scientific fact that climate change is occurring. Despite most of the country (and even world) knowing and accepting the truth that Earth’s climate is changing, Trump and many of his top appointees refuse to acknowledge it. This proves unpleasant and profound implications for the United States too, as not only do we risk physical damage like many of our coastal cities or even Puerto Rico with the numerous hurricanes we have had, our economy and leadership is also shaken, as our nation’s leader refuses to believe something so matter-of-fact as climate change. Earlier this month, at the Paris Accord, the agreement in which nations stand to acknowledge and deal with climate change, had even Syria sign, leaving the United States as the only country in the world that has not sign it, and will not sign it so long as Trump sticks by his ideals (or stays in office). The previous administration set several acts in motion in efforts of reducing greenhouse gases and our effect on the climate, all of which have been contested by Trump, in efforts to repeal those laws, to no avail as of yet. His idea that climate change is a “hoax” is baffling as his energy secretary Rick Perry, even notes that the “science is still out on whether or not human activity is the primary driver of climate change” (japantimes.co.jp). The EPA under Trump is rolling back on the climate change initiatives like noted earlier, including the Clean Power Plan or Clean Air Act, set forth by Obama and his administration. Scientists and federal agencies part of the National Climate Assessment in the US Global Change Research Program have published extensive research on the subject matter and are considered the most comprehensive and authoritative statements on climate science by the US Government. Even the US military is very cognizant of the existence of climate change and its potential to cause havoc to the world and also cost several hundreds of billions of dollars to deal with if something is not done to prevent or minimize the effects. It is embarrassing for a country so advanced and aware of world problems, to refuse to accept the existence of climate change, something that has extensive research on to prove.

How Technology is Helping with our Impact on the Environment

Technology is an ever advancing aspect of life, growing smarter and smarter with our passion and progress towards better artificial intelligence. With climate change an inevitable outcome of our society, our only choice is to ameliorate the severity of the change, by reducing our effect on the environment. Most countries in the world and much of the United States believes in the effects of global warming but meager efforts are being made to actually reduce our effect on the Earth. Even with the Paris Agreement, Syria sought to join the agreement to agree to make changes to be greener and help the environment, as everyone acknowledges this very real threat. This leaves the US as the only country in the World that did not sign on the climate deal. Because of the nature of our advancing technology, it is only natural that we would have it help in our efforts to alleviate our effect on the environment. There are already large scale technological efforts including Harvard University’s crop pollinating robobees as well as the prominence of driverless cars. The former is important too because bees have been dying at an alarming rate due to a disorder in colonies which could be correlated to climate change. Harvard’s robobees would solve the issue (especially in the event that the pollinating bees go extinct) by pollinating and ensuring that part of our environment is maintained. However, despite all these efforts at a greener tomorrow, the biggest and most important factor is each and every one of us, personally to watch our lifestyle. For example, we now have smart thermostats that use the internet to check the weather and adjust accordingly and are also linked to smartphones so they can be set on and off during set times of the day. Like if a family goes to work and school, heating or air conditioning is not needed between roughly 0700-1500, which saves a lot of electricity and heating bills. Amazon sells a lot of smart thermostats, many of which are compatible with Amazon’s Alexa artificial intelligence. As such, changing the temperature is as easy as saying “Alexa, lower the temperature to 65 degrees please.” There is also smart irrigation systems, as to avoid over watering your plants when you decide to turn the sprinklers on in the summer. These smart irrigation systems like Skydrop, utilise the internet also, to check weather conditions and are set to work on certain times set by the user. Skydrop knows not to activate the sprinklers if it detects that it just rained the night before for example. Overall, technology is being used widely to combat issues we recognise as problems and gives us better accessibility for it. If more and more people invest in these technologies, not only will they save money in the long run, it will greatly help the environment, which is crucial for our future, our kids futures, etc.

There Is No Timeline For Machine Learning

Machine learning has the capability to transform our future and then some. Currently, humans are working towards building machines that learn from themselves which could ultimately become so good at teaching themselves that it could eventually eliminate the human aspect. In today’s society, machine learning is becoming more and more useful across many different industries. We know what is happening now, and what could possibly happen in the nearest future, but what about the future in general? This answer is a little foggy. It is extremely difficult to foresee what machine learning and artificial intelligence will be able to accomplish. There is an endless amount of opportunities and it is a technology that is not fully understood just yet. This means the implications and the endgame for machine learning and artificial intelligence is unclear.

In order to prepare for the emergence of this developed technology, it is important to imagine the craziest possibilities and be ready to implement what is necessary to adapt our society. One article, written by Cade Metz, talks about the possibility of artificial intelligence being able to create artificial intelligence on its own. This idea stems from the reality that only about 10,000 people have the skills and knowledge needed in order to produce such innovative technologies. Google is behind AutoML, which is already successful at building an algorithm that can identify objects in photos more accurately than programs built by human experts. Eventually, computers may be able to create Artificial Intelligence by using a more advanced machine learning. It is already happening, and it is only a matter of time before human experts and Artificial Intelligence work side by side on a daily basis.

Today in class, we had the pleasure of witnessing a presentation by Frank Diana, and one point he made really stuck out to me. He mentioned how many people question when they should start preparing for the era of machine learning and Artificial Intelligence. The simple answer is now. The more complicated answer is that there is no official time to start preparing. This technology has already implemented itself into our lives without some of our knowledge. It is there when we are shopping, use a GPS app, use an entertainment service, and many other places. The thing is many people are infused with the convenience, therefore, they do not notice why or how it is happening. This means that those people are not prepared for the future of Artificial Intelligence and machine learning. Those who are educated in the subject are aware at how much guessing is going on. No one truly knows what is capable of happening or when it will happen. Most people will ask for a definitive timeline for the future, but the truth is, no one knows. This is either amazing, terrifying, or both. That is typically the way these revolutions happen. There are those who expect and accept change and there are those who simply ignore it. I found it amazing that machines and algorithms were able to learn from past mistakes but now there is Artificial Intelligence building those algorithms. It is simple mind blowing.

The main thing to take away from learning about machine learning is that development is nowhere near finished. There is still plenty to be discovered and the guessing game on time will continue. The key to the future is acceptance, the ability to adapt and a crazy imagination. This new revolution is happening and those who are aware will be better off than those who ignore it. Innovations, like Artificial Intelligence building its own algorithms, are popping up every single day and it will not slow down anytime soon.

An Unlikely Solution to Climate Change

Artificial Intelligence has been making waves in the past decade and the opportunities it unleashes are endless. AI is able to find, analyze, and understand millions of different articles, journals, and scientific reports. Because of this feature, AI would be able to analyze the data concerning climate change, the possible solutions or, at least, mitigation and it can suggest the best possible plans to implement. While AI has many stigmas and morality issues that come with its existence, it is obvious that it would be very beneficial to find a quick solution, which is especially important now. We do not have much time as people to still be waffling over the existence of climate change. We need to start thinking and acting on solutions that will help our planet in the long run, rather than just looking for short-term solutions.

Weather research and three types of climate change are the fields that are most affected by the introduction of AI. By using machine learning algorithms, the AI is able to analyze and sort data from extreme storms to identify early inklings of tropical storms and cyclones. By reviewing a wide set of data about past storms and their formations, the program is able to predict where future storms will form and can indicate which can help  people prepare for them better. The video below also shows a program that has the ability to predict when a flash flood would occur:

The AI can also prepare many different modules and scenarios for scientists in a short amount of time, so they do not need to waste time seeing if something would actually work and can spend their time creating something they know will work. The program would also have a smaller margin of error, so the calculations and predictions would be increasingly more accurate. Scientists can also use AI to produce a more accurate prediction of how long a storm will last and if it might produce a more dangerous type of precipitation, like hail. One downside to using AI to predict weather and climate phenomena is that the computer does not show the process it used to reach its conclusion, so a scientist is left to guess at how the program arrives at their prediction.

Another innovation being utilized in climate change research is cube satellites. Unlike the regular satellites we are used to seeing with cylindrical bases and large wing-like structures hanging out the side, cube satellites are much more compact. However, they are much more fragile and they have a much shorter shelf life once they are launched into space. This can also be beneficial. Because there is a need to change out the satellite more often, the software will be updated more often and the data can be updated. Additionally, we are able to change the course and objective of the satellite without the hindrance of delay. The satellite provide a live monitoring of climate change and its effects and can help gather more data to be studied.

By linking these cube satellites up with artificial intelligence, we would be able to gather present data and procure real-time solutions from the program. When we give the AI more data, it will be able to utilize machine learning to give a more educated and confident prediction. Additionally, we can give the AI data about the methods we have already tried that have failed and methods that have worked. As we give it more data, it is able to work around these failed methods and detect patterns in order to create a more successful method. By integrating Artificial Intelligence into climate change, humans will be able to slow the process and potentially reverse the effects of climate change in a more timely manner.

 

Machines “Learning” How To Steal Our Jobs

One of the biggest concerns many people have are whether their jobs will be taken over by the new and improved era of programs and robots. For the past few decades, plenty of jobs have become automated and this is what people who need to put food on the table are most afraid of. Some jobs that have already been affected, which is making the switch a little more real. Those may include or will include jobs in transportation and logistics, office support staff, sales and customer support staff and many more. These specific types of jobs will be replaced by autonomous vehicles, computerized check-ins for buildings, and chatbots and machines. Each of these new technologies have the ability to change the whole concept of unemployment. The question is, in what way will society and jobs as we know it have to adjust?

There are a few other career paths that may also be in jeopardy that some never thought of. For example, in the TedTalk below, Anthony Goldboom talks of a challenge presented by Kaggle to build an algorithm that could successfully grade high school essays. The winning team built one that was able to match the grade that a human teacher would give. This means that physical teachers or institutions may not be needed. As a society, we are already seeing college classes and some colleges being digitized and online. A machine is and will be capable of doing more work at a faster pace than humans do. This will only get more advanced as time goes on and as the technology progresses. Machine learning has the capability to adapt and become skilled in many different industries, which suggest that many jobs will be lost but overall efficiency can increase. Another example lies in the medical field. Many systems are able to spot diseases and tumors 50% more of the time than a human can. This means that these machines have a higher chance to potentially save more lives than current doctors or surgeons. The precision and certainty of this technology reduces human error, which can only help society.

Though many jobs will be replaced or assisted with machines and Artificial Intelligence, there will be those that require programming the technology or anything related to that matter will still be needed. The question then becomes, how do you prepare the current or future unemployed and employed to successfully adapt to the new world of jobs? There are potentially two answers. One is that current technology companies can implement a training program to help people learn new sets of skills. This means that we, as workers, would be redefining what it means to work. That is what people have been doing ever since automation started decades ago. When automation seemed to be taking over, new jobs presented themselves and more opportunities. By preparing, the working class now for a new future would be beneficial because this new era of technology will redefine our lives as we know it. We all will be impacted in one way or another and it is best to be aware of the change that is coming. The key may be to not only change ourselves but also redesign the system. This brings the second answer to mass unemployment, if inevitable, to light. Another solution could possibly be a universal income in order to help those who do not work to become completely lost. If plenty of people are out of work, with no money coming in, how will they live? What if there are no more jobs to adapt to? If a universal income were implemented then every citizen would have some sort of income and rise above the poverty line without a job. This also means the man who lost his job as a taxi driver would still be able to provide his family of five. Additionally, it could provide people with the opportunity of a passion filled life without stress of a job. It would be quite a long process to redesign the entire system of income for an entire nation, however, with the rise of automation and Artificial Intelligence, the government may not have a choice. This decision may have to occur in the next few weeks, months or years, but it would be valuable to have an idea of a solution before it is too late.

A TedTalk given by Garry Kasaparov, addresses how humans should work with intelligent machines instead of shying away from and ignoring them. A machine, IBM’s Deep Blue, was able to beat Kasaparov, who was a world champion, at chess in 1997, its early stages. He claims that what could be accomplished by computers or humans alone could be even more successful if put together. Imagine how precise your next doctors appointment could be in the near future? By normalizing the training of employees to program and use this new technology efficiently, means creating a world that operates at a new level we have never seen before. The modern era of machines and Artificial Intelligence indicates that our whole system of employment and income must adapt. We must modify and accept the upcoming society of work and redefine what it means to operate side by side with intelligent machines.

The Incredible Journey of Machine Learning

Machine learning has a great amount of meanings to different people. It has been around for years and now it is getting the attention it deserves. The technical definition of machine learning is “the concept that a computer program can learn and adapt to new data without human interference. Machine learning is a field of artificial intelligence that keeps a computer’s built-in algorithms current regardless of changes in the worldwide economy.” Many people think of artificial intelligence when they hear machine learning, and those people are not wrong but they are not right either. Essentially machine learning entails programming but instead of using code, one uses images and videos to build a model. A training set is selected, and the programmer chooses what imitates a positive or a negative for that specific set. Then they assign a specific model to use. The data one works with effects the model type and the size and quality of the sets. Additionally, it impacts the outcome. The process and technology itself is extremely complex and if something does not work correctly, the operation begins all over again. On the other hand, Artificial Intelligence depends on feedback as it interacts with the world and continuously adapts to new changes. There are layers to the overall aspect of Artificial Intelligence, which can easily be explained by this graphic:

Each level is a subset of the one before it, meaning one cannot properly function without the other. Deep learning carries out the machine learning process using an artificial neural net that is composed of levels arranged in a hierarchy. The particular network will learn something simple at the primary level, and then it sends the data to the following level. At the next level, the simple information is mixed with more data and becomes a little more complex. Then, it is sent to the third level. This process repeats itself at every level as the hierarchy becomes more and more complicated. Deep learning is essential for machines to be able to learn without a human labeling every single type of information that comes in, which is supervised learning. For instance, an endless amount of personal data is collected from social media accounts, hardware and software service agreements, app permissions and cookies. Businesses use this information for many reasons and it can be extremely valued. Not every element of the data is labeled which means it cannot be used to teach the machine learning programs that depend on supervised learning. To have a programmer oversee every data set that comes through would be extremely time consuming and expensive. Luckily, deep learning can help. It excels at unsupervised learning where the data is not labeled. Overtime, with enough information, deep learning can determine what is what, which helps machines learn without a human programmer.

Shockingly enough a children’s animation movie illustrated the abilities a robot could possess through machine learning. The Incredibles, a Pixar movie introduced in 2004, provides a good visualization of how machine learning and artificial intelligence work and the speed at which it processes real time information. Over time, it learns how Mr. Incredible fights and is able to determine ways to beat him. The villain, Syndrome, designed these killer robots, The Omnidroid, to eventually eliminate Mr. Incredible. However, over the years he put his prototypes up against other Supers in order to perfect his creation. As Mr. Incredible goes up against The Omnidroid the first time, it learned how he moved and predicted what he would do next. By doing so, it was able to delay Mr. Incredible’s victory. Even in 2004, moviemakers implemented this advanced technology in a children’s movie in order to show its future capabilities. A machine being able to learn in real time. As you watch the video below, pay attention to how Mr. Incredible initially jumps over The Omnidroid and how it then predicts him to jump over again.

Google has successfully combined deep and machine learning into a new program called AlphaGo. Go is an ancient Chinese board game which is allegedly the most complex and subtle of all board games. This is not as typical as chess, where a computer can calculate every possible move thousands times fast than a human. In Go, the possible moves are endless, which means no computer can handle trying. However, researchers in the UK were able to teach a computer program to play Go, but it also has the ability to learn from its mistakes. It used deep and machine learn to study which moves left it vulnerable and which ones lead to victory. In the beginning, there were a lot of mistakes made, but this was a good thing because the program was learning. The more it played against humans, the more it learned. As time went on, it played against more skilled players, and in addition with those games, it played matches against itself. When the researchers put AlphaGo up against itself, the program became much better as it was able to compete against a player at the same skill level. Eventually they put AlphaGo against the number one player in the world, Ke Jie, and beat him in five games out of five. After that, there was no one else left to beat in the world. AlphaGo was able to learn from itself and become the greatest Go player in the world, and it is just a computer program. If it is already the best, how much better could it get? AlphaGo Zero.

The opportunities to use machine learning are endless and highly effective. If in 2004 a children’s movie can display its basic capabilities then it is astounding to see how far it has come since then in the real world. The news of AlphaGo and AlphaGo Zero are surprising because it was not expected that this technology would advance this rapidly. These machine learning programs is truly a breakthrough breakthrough and it will continue to improve in the future.

Ethical Implications of Autonomous Vehicles

Autonomous vehicles will one day become the normal way to travel. However, there are still plenty of ethical issues and dangers this new technology holds. It is easy to forget about the impacts technology has on society because everything is innovative and exciting. Nevertheless, the ethical implications must be discussed in order to avoid potential accidents or tragedies. The possible dangers might include the likelihood of a hacking or if the vehicle does not make a decision fast enough. Some of the ethical effects can be what kind of decisions should be made in certain situations and if programmers should have transparency with consumers, so they know exactly what the autonomous vehicle entails.

These cars rely on machine learning in order to evaluate situations and make a decision. The computer is simply not given a set of rules to follow. Instead, it is fed images of objects – for example, a pedestrian, a ball, another vehicle, etc. – and tries to guess what that object is. In the beginning, it will guess wrong. However, as time goes on, the program adjusts itself, and continues to try as more information it is given, it begins to learn what is what with the help from the cars sensors. If there is unidentified object in the road, the car should reduce speed or stop altogether. Another way for the vehicle to learn is by feeding it certain traffic information and the programmer would say the right way to get out of it. The algorithm will learn from that, along with other aspects of a situation, and determine the correct way to get out of it. One of the main issues is how fast these computers will be able to make decisions. While humans drive, it takes a split second to make a mistake and terrible things could happen or it takes just as long to avoid that. Most people have good reflexes and are able to avoid a tragedy. Autonomous vehicles must have that same ability to avoid accidents. Machine learning and quantum computing must work together in order to allow those cars to make effective and quick decisions. The programmer must teach the computer the basic rules of the road and allow the machine to learn impactful and successful ways to avoid accidents.

Another issue that stems from autonomous vehicles is the possibility of someone hacking the program of one. Skilled hackers are able to break into almost anything, so how is a vehicle any different? Software and algorithms will power them, which can be susceptible to malicious people who have the intent to harm others. It might not be a trend now, however, as this technology becomes more normalized, anything is possible. Car and technology companies claim that the consumers will be safe from hacking, however, it would be in the best interest of the consumer to not take their word. Some in the industry have waited to announce a recall until it became cheaper than paying the wrongful death lawsuits. It would take enough steps in the right direction for car and technology companies to act in an ethical manner. It would be best to not trust their word. As the conversation about hacking becomes more popular, there should be laws requiring cars to have certain types of encryption and cybersecurity in order to protect the passengers of autonomous vehicles. These companies should also consider the approach of a greater transparency with their consumers. That way, if they are ethical and genuine, consumers could trust using their products, in this case an autonomous car.

Though autonomous vehicles will be able to solve many problems and subtract human error, it is important that it does not replace it with programming errors. It is also essential that the algorithm learns in an ethical and correct way. It may take time to determine what that is, however, the minimum amount of accidents and casualties is desired. Car and technology companies must implement sophisticated cybersecurity to protect against any type of hacking that might take place for any reason. There is a long road ahead when it comes to creating the software in the right way. That way when it learns, it learns in a correct and moral method. Machine learning plays a big role in the success of autonomous vehicles and though there will be problems, it would be beneficial to minimize them as much as possible.

Machine Learning Is Learning About You

In the advertisement industry, machine learning could be a great asset for a company. It helps determine patterns among consumers, which allows the marketing team to alter advertising in effective ways. However, when it comes to advertisements online, targeted ads are becoming a huge controversy. It means advertisement companies track what you do online in order to suggest certain websites or products. They use your past searches as a base for what you might click on in the next five minutes or next week. They also collect data about your demographics in order to determine how much you can afford and when you might be able to afford it. This information could come from any company that sells your information to third party companies or from social media accounts – Facebook, Twitter, Instagram, etc. With the abundance of data used in order to successfully draw you in, it is obvious a human is not behind it, but machine learning. It works by collecting a huge amount of data in order to make accurate predictions about what you are interested in. The more information the algorithm has, the better it learns and the more accurate it becomes.

By using machine learning, marketing teams and companies gain a huge advantage. They are able to learn more about who their consumers are and how they think. It helps, “marketers analyze countless signals in real time and reach consumers with more useful ads at the right moments.” Jeff Rajeck creates a systematic outline that shows how to integrate machine learning into a company. First, one must find the features of the ad – platform, the copy, photo, etc. Next, one has to identify the results of an ad. The third step is to gather the right data that will cover the features. Once one has the correct data, they can then pick a machine learning program. Then it would be beneficial to split the data in order to have one set for learning and the other for testing. The sixth step is to run the algorithm and see the magic happen. It will then show predictions for which ads tend to draw in the desired consumers. The system will be able to improve itself over time and become more accurate with the data it collects. This ultimately changes the whole marketing industry allowing for more audiences to be reached.

At times, machine learning can get too good at its job. A Target advertisement system was able to determine a teenager was pregnant by her web searches before her father found out. They sent coupons to her house in hopes she would shop there and become a lifelong customer. When a customer purchases from Target, they create a profile, which assigns a Guest ID number that includes their credit card, name, or email. It also collects demographic information that Target acquired from the consumer or bought from other sources. The young mother-to-be was most likely researching things related to her pregnancy. If she was using Google, then they presumably sold that information to Target. Everything we do online is tracked and the data is sold to other companies in order to produce more personalized advertisements. Target statistician, Andrew Pole, analyzed historical data of women who signed up for Target baby registries. By using those past purchases as a base in a test, patterns began to emerge of specific products pregnant women bought. Pole’s system was also able to estimate when their due dates were within a small window, which allowed Target to send out coupons tailored to the stages of the pregnancy. People became aware of how in depth Target was, and were taken aback at how much they knew. Now, the company mixes their targeted coupons and advertisements with random ones, therefore, it is not as obvious. The more information a system has, the more accurate their predictions become.

Though using machine learning in marketing could be extremely beneficial, there are a few ethical implications that arise. People usually love tailored material in order to make their shopping experience much easier, however, is it worth it if you are constantly being tracked? Is it worth it if your web history is being sold to third party companies? Is it ethical for companies to make a profit off consumer information? These are the types of questions people must ask themselves and if the answer is no, then they should take the necessary steps in order to protect themselves. Machine learning will continue to be a controversial topic and the ethical implications must be discussed.

Amazon and Groceries: How Amazon can put the hurt to supermarkets.

Amazon is poised to take the super market industry by storm, when it revealed late last year that it was test running a grocery store. This grocery store utilizes technology called “Just Walk Out” technology, which is a combination of computer vision, deep learning algorithms and sensor fusion. What this does it allow for the artificial intelligence do scan your phone when you enter the store, and keep up with the items you take and put back onto the shelves in real time. So even if you take an item and then put it back, you will not be charged. Then instead of waiting on line, you just have to walk out of the store and your amazon account will automatically be charged and a receipt sent to you phone. This is new type of store has the potential to utterly destroy not only super market chains, but almost every kind of brick and mortar store available. Companies like Amazon will only need a fraction of the employees to fully operate the store as the previous need for cashiers will be gone. The only people needed will be janitors, people to restock the groceries and an overall manager to address any issues. And as this spreads to other stores like game stop and other kinds of retail, people will begin to lose jobs at a very fast pace as more and more jobs are simply no longer needed because of technology simply being better.

So one question remains, how do new comers compete with giants like Amazon. Well the short answer is they have to have everything connected to the internet. To describe this best i suggest going to 5:30 in the video above. What Taylor does to solve the problem of having to turn away walk ins, is symbolic of what the age to come is going to bring, utilization of the internet and adapting it to your needs. Taylor describes how he has a button at his place of work that they press every time they have to turn away a walk in customer. This builds a map for them of when they need staff as opposed to when they don’t. This allows them to place they employees on the clock when they are needed most and have less people on when work is slow. Adaption and thinking like this will allow smaller stores to compete with larger companies like amazon. And both are going to be the future of retail around the world.