This began with a company in the UK called Cambridge Analytica. They were working on using data to predict and influence human behavior. This can have a lot of applications in areas like advertising where people’s purchase decisions can be influenced. But it also had another application – influencing votes in political elections. Cambridge Analytica started mining user data from Facebook and using it on various elections. Whistleblowers claim they targeted elections in Phillippines, few countries in Africa, UK’s BREXIT vote and the 2016 US elections. Political candidates raise a lot of money for campaigning and are willing to spend it to increase their chances of being elected. This caused panic among countries on the possibility of foreign interference by enemy states.

The next action was controlling the pipeline a.k.a. the social networks where people consume the information. This began a long brainstorming moment for all countries to add laws to govern social media networks both foreign and domestic. China was ahead of the curve. China requires an ICP (Internet Content Provider) license for every website that can be accessed in China. Obtaining the ICP license requires you to be a Chinese citizen, legal resident, or Company registered in China. Or you can find a local agent who acts as a middleman to get you an ICP license for your domain name. Given the velocity at which they are granted, they seem almost automatic (not much vetting) but can be easily revoked when a website is interfering in local affairs and gets the spotlight. 

The United States has a law that grants legal immunity to social networks (content distributors) from lawsuits on the account of harmful / illegal / offensive content from its users. The US is trying to overhaul this law to make its platforms more accountable. But the US is also trying to ban Chinese social media apps (TikTok and possibly WeChat). Other countries like India have already banned apps from China. But the US is the leader of the free world where censorship does not exist. Its main attraction is free and open markets. While a handful of other countries around the world blocked services (UAE blocked FaceTime for instance, where as Turkey blocked Wikipedia), the US was not a regular country. It was considered the place of unrestricted commerce and growth. But that may not be the case for long. Social networks are joining the list of WMD (Weapons of Mass Destruction) and now internet censorship is becoming a national security concern.

The internet has many applications from communication to shopping to booking travel to sharing scientific research. But one of its applications (social media and news consumption) has threatened its existence as we know it. It will still exist but may never be the same open space that encompassed the entire world.

5G is the next generation of technology that will power the telecom industry and mobile internet consumption. Carriers in every country will be upgrading their infrastructure in the coming years to enable 5G in their countries. Huawei is leading 5G development with the most advanced equipment today. Many countries are planning to buy hardware for their infrastructure from Huawei, except the US. The US Government fears having an infrastructure built with Chinese technology. They believe that the Chinese government could use its political influence on the Chinese company and lead to planting spyware on the infrastructure, leading to US information ending up in China. Given the fears of the US Government, they don’t want to adopt 5G just yet. The US would rather wait for American companies to develop the infrastructure without Huawei hardware. The US is also influencing other countries (mainly in the European Union) to avoid using Huawei equipment in their infrastructure.

Broadcom and Qualcomm are American companies with Qualcomm being the one that does a lot of R&D and makes 3G and 4G chips for phones. However, both companies are not doing great and a merger seemed like it could grow the companies and make them stronger. Hence Broadcom put a bid to buy Qualcomm and the future looked good for both the companies. Typically, when an acquisition is proposed, the US Government, specifically CFIUS (Committee on Foreign Investment in US) can step in and intervene if the acquisition affects US national security. In the case of Broadcom buying Qualcomm, there was no question of national security as both companies are American and there is no foreign company involved. But this would mean that as a part of restructuring post-acquisition, Broadcom would decrease money spent by Qualcomm’s R&D team, leading to slower progress. And we have seen that US would not buy 5G infrastructure from Huawei and would not let its allies buy from Huawei either. This means that it really does not want Qualcomm’s R&D spending cut. If this happened, it could hold off upgrading its infrastructure, but would not be able to hold off its allies in staying on old infrastructure. So the US Government blocked the acquisition completely.

This shows that the government could step in on domestic transactions and even cause losses to American corporations for the sake of politics. While technology has typically transcended boundaries, it would be interesting to see how regulations create silos of technology and prevent borderless sharing of technological progress.

Aging has to do more with Physics than Biology. If you buy a new car, it will wear down over time. You will need to repair some parts and replace others. The human body also wears out and needs repairs. Cell division occurs in the body as old cells die and new ones take their place. Sometimes old cells stay around. These are the senescent cells. They stick around and cause harm to other neighboring cells, in turn causing a lot of problems. We have learned that killing these cells leads to healthier lives. We could soon see pills that you can take to kill the senescent cells in your body, resulting in a overall healthier life with lesser sickness.

Another aspect is decreasing production of NAD+ in our body as we age. NAD+ is a useful coenzyme produced in our body that keeps our body functioning correctly. Scientists have tried making pills that introduce extra NAD+ in our body. But this did not work because it was unable to reach the places in the body where it needed to go. We have recently learned that we could inject other substitutes to NAD+ in our body which is able to reach the right areas, and that our body is able to convert into the NAD+ coenzyme. This means we can have plenty of NAD+ in our body as we age, keeping us healthier.

Finally, we are making progress towards stem cell research. With regenerative medicine, we can study how stem cells create tissue and design therapy to introduce new stem cells in the body that can be made into tissue. This will further help in having a healthier life. None of these technologies are the single solution to combat the aging process, but all of them combined can be used to slow the aging process and increase the healthier life spans in a person’s life. We are seeing a lot of advancements in this area and it might be the next big technological solution that shapes our lives.

In order to tackle the dramatic shift in how future productivity will function – where more of the work is automated, we must be willing to take a hit on the meaningless yearly growth numbers and start working towards completely different metrics and frameworks that define growth and productivity in the future.

Our education system was designed during the industrial revolution. The factories had assembly lines, and we replicated those in the classroom. We had grades 1 through 10. Every year you progress to the next grade, and are fed with all the information from sciences to arts. The information is more detailed in each of the subjects as you progress through the grades. At the end, you come out of the assembly line of education – to work in the assembly line in factories.

Technology has already taken over repetitive tasks in the assembly line, and is now taking over tasks that require a little bit of processing (like driving fleet of trucks across the country). In the future, it will take over more tasks that need complex processing of information and decision making. What we must remember is that technology taking over these tasks is not a threat, but a time to celebrate success of human creativity. Humans have created these machines that can do our tasks for us. We must be happy that we don’t need to do those tasks anymore, and can focus on better things that matter.

We must start to get out of the mentality of working, earning money, paying taxes, contributing to GDP, and increasing the numbers every year to show growth. We must reevaluate the purpose of society, what we want to accomplish as a human society, what are the things that matter, and how we want to work towards that goal. Then we must use automation to the fullest extent everywhere to get work done for us, while we focus on the bigger picture. Yes, this means present jobs would not be available, and that will result in people not being able to pay their mortgage. But those problems are created by the current framework used by us. If we change the framework, we do not have to worry about those issues anymore. We could collectively contribute to productivity at a higher level while leveraging the machines, and reap the results to support the society with all the people in it.

There are numerous possibilities on tackling this dramatic change in workforce. However, if we keep holding on to our current models and refuse to analyze the alternatives, we will not focus on the things that matter, but will continue to focus on generating more revenues, having high GDP numbers, and “growth”. This becomes even more disastrous as the population continues to grow significantly and they go through the same old education system of the industrial revolution that would train them to obsolete tasks that have been automated. We must start to invest in alternative education systems that foster creativity and thinking. We must focus on just one skill – problem solving. Then we must leave individuals to pick their own domain of passion where they apply the critical thinking and problem solving skills. As the population continues to grow, we must make the shift otherwise we will have a bigger burden to support while automation takes over and the people are not ready for it.

The growing population adds challenges to this problem. If we see massive unemployment with the current workforce that we cannot handle, we are clearly not going to be able to support the additional population. Hence, we must act on a better education system that is dramatically different, and push the models to developing countries with high population growth. Only if we act on the change that is coming, we will be able to tackle it and embrace the positive things that come with it.

When cars (horseless carriages) were first invented, people experimented with different sources of fuel like oil and electricity. Due to lack of advancements in battery technology, oil was the chosen fuel. Oil has also evolved (whale oil to leaded petroleum to unleaded petroleum to unleaded + ethanol mixture) but the oil cartel has made sure that they stay the source of fuel. The OPEC (Organization of the Petroleum Exporting Countries) had cut oil supplies in the 1970s leading to shortage of fuel and unemployment, which led to recession in many countries like the US. This caused the US to become more active internationally and open military bases in other countries (mostly oil producing countries), so the US keeps getting oil and the crises of the 1970s never repeats. The US consumes 18 million barrels of oil every day and only about 8 million barrels is domestic (so most of it comes from OPEC). While the US focused on opening military bases overseas to ensure oil supply, Brazil took a different route. They pushed for FLEX vehicles (Flexible fuel) that worked on petroleum, ethanol or a mixture of them. Consumers could choose if they wanted to fill their cars with petroleum or E85 (a popular ethanol + oil blend). E85 costs about $2.10/gallon in California right now compared to $3.10/gallon for unleaded gas. Hence its over 30% more economical to choose E85. The mixture does reduce the number of miles your car travels for every gallon, but its much more cheaper and burns cleaner compared to oil (a.k.a. better for the earth).

Despite the advantages of FLEX and its success in Brazil, the US did not see this. The reason was oil cartels spending millions of dollars in campaign contributions and blocking legislation. They also own most gas stations (and control independently owned gas stations) which allows them to only sell gas and prevent ethanol from being sold. So the oil cartel successfully blocked a more clean (and cheaper) fuel from being accessible. While countries like Brazil enjoy choice between kinds of gas that go in their FLEX vehicles, the US is stuck with oil and spending billions in military bases overseas to ensure oil interests. But all of this is about to change with Tesla’s innovation in long range electrical vehicles.

Tesla’s Model 3 has about 400,000 pre-orders and over 1 year wait for new orders. The $35,000 car will provide freedom to the people (freedom from the shackles of the oil cartel) and reduce the cost of fuel by over 60% while keeping the environment clean. Since battery technology can now allow 200 miles of range, its more practical to use electricity as the fuel source. Many car makes have made affordable electric cars now and government is providing incentives to buyers. Tesla has proven that they are desirable too (with their pre-order numbers) and this finally means that we can break free from the control of big oil. Silicon Valley is known for disruptive innovation, and Tesla has extended that to transportation and taking on big oil.

In the next few decades, we should see the number of electric cars growing and gas powered cars reducing. This will finally end the century long grip of the oil cartel.

There have been advancements in hacking car technology which is enabling car thefts using high-tech hacking. Some examples include planting signal catchers in public parking garages and capturing the unique fingerprint of fobs when owners lock and unlock cars. Thieves can then use these captured fingerprints to create fake keys with the same fingerprint and use it to unlock and steal vehicles. There are also hackers that have demonstrated that they can remotely engage breaks in moving cars or prevent them from breaking, by hacking into the on-board central processor in the car. While this is not common, they have certainly demonstrated the vulnerability with technology powered cars. Even Tesla’s Model S was hacked. The attackers could perform all the function that are performed by the on-board touch display. When Tesla was notified about this, they pushed a software update to patch the vulnerability.

Traditional car makers like Ford, GM and Toyota still build cars the old way. They are manufactured, sent to the dealership, and sold. Thats the end. Customers then bring them for servicing periodically. Tesla on the other hand has made cars into a subscription service. Its like owning an iPhone, where you download a new version of iOS every year that gives you new features on your phone. All Tesla cars get periodic software updates that give them new features like AutoPilot (their assisted driving feature) and other enhancements. They plan to make their self-driving feature a subscription service as well. This makes sense as the capability relies on new data that is collected as people drive everyday and it makes the car smarter over time. This also has another advantage. Fixing security vulnerabilities with software updates. If a researcher finds a way to hack into a Tesla, the company can push a software update to patch the exploit. Traditional car makers on the other hand would have to recall the vehicle, or ask millions of customers to take them into a service station. Or they could even ignore the vulnerability and fix it in their new model for the subsequent year. Cars have transformed from mechanical marvels to technological gadgets and Tesla is the only one that is treating cars like smartphones or computers. The traditional auto makers treat their technological cars like mechanical cars, leaving them open to vulnerability.

Whenever there is a flaw, there are companies to address the gap. With traditional car makers not paying as much attention to these issues (even though they are slowly starting to), companies like Viper are building security kits that can let you control your car (lock, unlock, start engine, etc) using their app. They sell subscription services and provide alerts on theft, GPS coordinates and more. There are new companies like Viper popping up everyday that are addressing this issue. These devices cost as little as $100 and can also be self-installed if you are willing to read up the manuals and buy some tools.

While the vulnerability of cars is not a major concern today, it definitely will be one in the next few years. Imagine a bank van carrying money being hacked to break at a certain location, or a Presidential car being hacked. Even mass hacking of all cars in a city can cause chaos. This is a big security problem for the future and car makers need to start thinking and acting on this issue. Tesla has a head start on this, but all other auto makers need to rework their model of making and selling cars. Meanwhile, security companies like Viper will emerge everyday to address the future needs of car monitoring and security.

Some of the largest banks in the US have collaborated to create a centralized database of consumers using their banking products and share information such as fraud or misuse of bank accounts. This is the EWS (Early Warning Services) system. Banks such as Bank of America, Wells Fargo, Chase, Capital One and others have collaborated on the EWS system so they can share data and reduce risk. Now EWS has announced that they are launching their own mobile payments app called Zelle. The landing page of Zelle claims that it will allow users to “send and receive money in minutes”, which is possible as the service is run by the big banks. The main problem with current apps is that the money goes from the sender’s bank account to the mobile payment provider’s bank account, and then to the recipients’ bank account. This causes some delay in transfers (usually a few days), even though you can see the balance in the app immediately. Zelle might be able to eliminate this delay as its run by the big banks, and money transfers could be instant. So the sender’s bank account would be debited and recipients’ bank account could be credited in minutes. This would also eliminate the middle-man (transfer to mobile payment provider’s account), hence reducing costs.

Zelle seems to be a better product because of its speed, but the question remains if consumers would use it over existing apps. A majority of the consumers using these services are the younger generation that care about the social impact of the products they use. While they pay attention to costs, they also pay attention to who benefits from their business. If they don’t want the big banks to be profiting from their business (because of the perception of big banks), then they might decide to ignore the service and stick to existing apps like Venmo and Square Cash.

The new Zelle app is planned to launch in October 2016. More information can be found of their website here.

Machine learning has a plethora of applications. One area in which machine learning is being used is the field of medicine. Researchers perform experiments in labs to study effects of medicine on different animals. When a drug works on a monkey or mice, they start a clinical trial on humans (after endless amounts of paperwork). If the clinical trial is successful on a diverse sample of subjects, then the FDA approval starts. After FDA approval, the drug can be marketed for mass distribution across the country. At this point, the drug makers spend money on marketing, sales representatives, providing incentives to physicians that agree to prescribe the drug, and advertising on TV and the internet. The drug is known to treat a certain condition, and has a list of known side effects. Millions of people across the country take this drug and it works for most of them. This is a system that has been in use for decades.

This seems to be working fine. So where is the problem? The problem lies with studying effects of multivariate medicine. A lot of people consume more than one medicine at a given time. They can be on multiple prescriptions. We study the effects of a single medicine to understand what it does to the body (its cure and side effects). However, when you consume two or more medicines together, you have a multivariate problem. The equation contains two or more variables, each having an effect, but together with other medicine, having a different effect. With each medicine you add (another variable), the problem gets harder. Medicine A can have some effects on a person. Medicine A + Medicine B can have a different effect. But when you mix Medicine C, the results change. You can have endless permutations and combinations. While you can study the effects of this on mice in labs, it would take an en eternity as you would need a sample of mice on Medicine A + B, a sample on Medicine A + C, a sample on Medicine B + C, a sample on A + B + C, etc. This would become exponentially harder when you add each variable.

So how do we solve this problem? In the last few decades, we did not solve this problem. We focused on researching new drugs, doing trials, getting FDA approval, and marketing. However, with new breakthroughs in Data Mining and Machine Learning, we can use computers to predict the outcome of these combinations with a decent confidence level. We will not need an eternity and endless mice, we just need some computers in the cloud crunching numbers. Why do we care about this now? It’s because this will help us understand effects of medicine taken together. So a patient can go to a computer, enter the list of medications, and know the real list of side effects that the patent faces when that combination of medicine is taken together. Some medicine taken together can have lethal effects even though taken separately, they are safe. We do know that some medicines don’t go together. But we don’t have a complete list of every combination of drugs that are FDA approved. Furthermore, combining some drugs can have interesting effects. They can be the cure for a disease that we did not have a cure for. So by using Machine Learning to understand side effects for the machine, we will also discover combinations that would be cures for diseases that we currently don’t have a cure for. We will be able to use the knowledge of medicine that we have accumulated by lab experiments, and generate exponentially more knowledge about medicine by just computers crunching numbers in the cloud.

Machine Learning is being used in a lot of fields for different purposes, and now we will be able to accelerate discoveries in the field of medicine and learn about side effects that we did not know about.

We have been able to make tiny micro-sensors that are smaller than a nickel (a small coin), that can record data for several months without a charge and transmit that data back to us. These micro-sensors are getting more affordable everyday. This means that soon we will have these tiny sensors attached to hundreds of birds that fly around. This will give us data about the weather, the level of carbon-dioxide, carbon-monoxide and countless other gasses in our atmosphere. We will be able to use the data over long time periods and co-relate the changes in weather with different levels of gasses in the air. It will help us learn the effects of our activities on the planet over time. It could even unravel different ways in which we can prevent climate change or tweak our behavior in minor ways to have a big effect on the environment.

Besides birds, these tiny sensors can be attached to almost anything. They can be attached to cars to monitor emissions over the course of a day. Along with location information, it can give information of traffic congestions in certain areas, the emission levels, and suggest ways to act on that information. They can even be put on roofs of houses in communities to collectively understand effects of housing communities on the environment. We could have information from different sensors encompassing the entire globe available to everyone, just like we do with the web and Google. This data would help us learn about cause-and-effect of various things that can provide solutions and understandings of problems that we might not even be aware of today.

In the future, you might be able to pull out your smartphone, put a pin on the map and see different things like air quality, carbon-dioxide in air, the noise level, and much more, all in real-time. Researchers could use this data over-time and come up with different solutions for a more sustainable future. Hopefully, it wont be long until we get these micro-sensors accessible to everyone that wishes to use them and provide data back to a central repository.

It is becoming easier for hackers to break passwords and hijack accounts. We have resorted to using more complex passwords than we cannot remember, and relying on password manager apps to store them. This is becoming very inconvenient. To solve this problem, many companies are working on the next generation of passwords. EyeVerify has developed eye-detection software that detects eye characteristics using a picture from the camera, and generates a password based on the characteristics. They call it the EyePrint. They also detect features like vein patterns in the eyes. So when you want to login to a service, you can simply snap a picture of your eyes and be authenticated. MasterCard is also working on a similar approach. They are using selfies for authentication. This involves analyzing more facial features like position of eyes, nose, mouth, etc. MasterCard believes that this is the future of passwords.

These technologies have its flaws as well. For example, the eye detection software might not work well if you are in a room without lights, or if you have red eyes due to lack of sleep. But its a start. MasterCard’s selfie software might also fail if your appearance changes. It could be things like growing a beard or mustache, or even characteristics like natural aging. Hackers could also find your selfies on Instagram, print them out and hold them in front of a camera to authenticate as you. These are all possible ways to break the system. But again, its a pretty good start at coming up with alternatives to passwords.

As humans, we recognize each other by seeing faces. Our brain processes facial features when we see someone, and then identifies the features to a person. When the person looks slightly different, we can immediately notice the difference. If they look like someone else, we can tell, as our brain compares their features to the features of someone else. While these technologies have its issues, passwords do as well. Its time for the next generation of passwords, and they will likely be your facial features.