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Google Research and Development Projects
TC
American Public University System

Google Research and Development Projects Google has an arm of their company called Project X that is tasked with researching and developing new and evolving technologies. When many people think about Google they simply think of the company as a search engine and web mail hosting company. The fact is that Google excels in those areas but is also on the forefront of new technologies that have the potential to change how people drive, how internet services are deployed in remote areas, how home environmental systems are controlled and how internet orders are delivered (ExtremeTech, 2015). In particular, Google’s self-driving car, DeepMind artificial intelligence, Project Wing drone, Project Loon balloon internet and Nest home automation technologies show promise to improve the quality of life for many in the world. Google’s research and development mission is to consolidate information from across the world from many sources and then make that data both useful and available to all internet users (Spector, Norvig & Petrov, 2015). Additionally, Google uses the technology to improve existing goods and services as well as improving the environment through clean energy initiatives. Google as a company is focused on rapidly developing and implementing new technology in all areas but the research but the research and development arm is hyper-focused on technology innovation (Research.google.com, 2015). Newer technologies that are developed may impact security, safety and have other unintentional effects. Along with the development of these technologies, environmental, legal, safety, security and moral evaluations and discussions need to occur. These technologies obviously have the capacity to both improve the quality of life and the environment, but they can also have negative impacts on society that need to be considered.
Self-Driving Automobile Google’s self-driving car is an autonomous electric powered automobile that uses navigation, cameras, sensors, lasers and other advanced technology to take control of the vehicle. This project was an evolution from a DARPA grand challenge for the creation of robotic vehicles early in the 2000s (Gibbs, 2014). Google’s smart car can self-drive, navigate to a desired location, self-park and notify the controlling user when maintenance is required. Google is making sure that these cars are smart and internet connected, so that users of the car can interact with their cars (della Cava, 2015).
One of Google’s biggest problems with the self-driving car is that many people actually like to drive (Xavier, 2015). Americans, in particular, spend large amounts of money to personalize cars with accessories and upgrades that may not be available on self-driving cars. As with any internet technology, there is always the potential for vulnerabilities to exist and for the technology to be hacked which can open the door to systems being damaged or taken over by criminals or terrorists so security would need to be addressed. Navigation systems would have to be updated and be very accurate to be able to support navigation to all locations that the user would need to get to (Gibbs, 2014). Another hurdle that the self-driving car has is legislation. Currently, laws are very unclear about the use of self-driving cars on public roads. California does allow some testing and operation of the self-driving car on public roads as long as there are manual overrides (Gibbs, 2014). There is always the possibility that a malfunction or some other system anomaly could trigger a collision which would affect law enforcement and how fault for collisions is applied. Even if the technology takes off and is adopted, there would be a long period where both standard and self-driving cars would share roadways, adding to the legal complications. Additionally, there would also be the question of how insurance companies would manage and apply this type of risk.
A main concern would be if the system has to make a decision on how to handle an unavoidable collision (Bailey, 2014). Who or what would be sacrificed? In some situations, an accident occurs where someone dies. Do we want to have machines making these types of life and death choices? Additionally, these vehicles would need to be constantly updated to avoid the possibility of being hacked and taken over by others. With that being said, I really don’t think that the technology itself is going to be difficult to implement as much of it already exists and is in use in some form. The real concern will be more of how the technology is introduced and implemented. For the most part, systems in a self-driving car would be very efficient and in most cases be much more reactive to road hazards and other vehicles on the road (Bailey, 2014). With that being said, I think that these cars need to have manual overrides and be able to be manually operated when conditions require human decision making. Legislation would also need to be updated to set specific parameters for the operation of self-driving cars such as being under human supervision, having a kill switch that would stop the car in an emergency that was missed by the onboard systems. In theory, accident rates should be lowered which would require lower insurance premiums but procedures would need to be developed to determine how accident fault would be determined and applied when self-driving vehicles are involved.
There are certainly both positive and negative effects of this technology on society. Self-driving car technology will allow users to summon a car that has been self-parked to pick the driver up from his specific location. This will remove the burden of finding parking and reduce parking limitations as cars can be parked closer together when no door needs to be opened. This technology has the potential to ease traffic congestion as well because the cars would be able to work in concert with other smart cars to optimize speed and spacing which will significantly improve commute time and reduce congestion (della Cava, 2015). The fact that these vehicles run on electric power rather than fossil fuels combined with a reduction in traffic congestion and potential to end gridlock these vehicles will put a huge dent in harmful emissions (Gibbs, 2014).
In an article by Ronal Bailey, the author states that “People a generation hence will marvel at the carnage we inflicted as we hurtled down highways relying on just our own reflexes to keep us safe” (Bailey, 2014). Bailey backs up this statement by stating:
More than 90 percent of all traffic accidents are the result of human error. In 2011, there were 5.3 million automobile crashes in the United States, resulting in more than 2.2 million injuries and 32,000 deaths. Americans spend $230 billion annually to cover the costs of accidents, accounting for approximately 2 to 3 percent of GDP.
I don’t believe that there is a moral imperative for human driven cars to be replaced by computer self-driven cars. I do agree that there is a cost to human driven cars in both money and lives. Cars have been a staple of American culture. People tend to personalize their cars as an extension of themselves and will spend a lot of time and money on them. Yes, there will be accidents, injuries and even fatalities, but the fact is that some Americans simply like to drive. There will always be those that will want to be in control of their cars and be able to drive (Xavier, 2015). There are concerns that as machines begin to be smarter and take over tasks that humans historically have done that they will begin to take over everything.
Google DeepMind Artificial Intelligence Technology Google’s DeepMind research project is an effort to develop various artificial intelligence (AI) technologies. DeepMind is using AI technology to develop machines that can actually learn by reading data from large annotated data sets using a method known as deep learning (MIT Technology Review, 2015). DeepMind’s deep learning efforts have made its progress due to the development of neural networks and large annotated databases. Neural networks mimic the behavior of the human brain and how neurons have the ability to learn by making connections to process the information that we see, hear and touch. Researchers in Singapore have used this technology to develop two-dimensional neural cells in software that show promise in propelling AI technology forward (MIT Technology Review, 2015). When these neural networks are combined with large annotated databases AI systems can read the information and learn. For example, DeepMind researchers in London are using Daily Mail and CNN databases that are annotated in a way that their AI machines can read articles and then can answer questions based on what was read (MIT Technology Review, 2015). DeepMind technology has applications including robotics, facial recognition, voice recognition, fashion, forecasting and economics. Google is currently using the technology for fraud and spam detection, handwriting recognition, image search street view detection and translation (Shead, 2015).
Although Google’s DeepMind technology has made huge advances, it has not yet been able to replicate the human brain’s capability of learning, storing and processing information. Technology will need to advance quite a bit more to truly have the learning and thought capacity of the human brain. One of the biggest concerns about the development of AI technology is that at some point machines may become more intelligent than humans which many see as a very real threat. Hollywood has put forth movies like the Terminator and Ex Machina have shown the fictional repercussions of what may occur as this technology advances and machines become self-aware and more intelligent than humans (Shead, 2015).
To overcome limitations of the technology that will be needed to create true AI, systems will need to continue to become smaller, faster and require less power. With Moore’s law we are seeing the doubling and shrinking of processing power every 18 – 24 months so it is only a matter of time and new technological advances that will allow technology to be woven into very intelligent neural networks that could support true AI that could be comparable to the human brain. As for managing concerns over machines becoming self-aware and too intelligent, engineers need to develop specific methods that would prevent machines to prevent machines from progressing beyond the scope of required functionality. This could be done in software and even a hardware kill switch where machines could be shut down like with the Google self-driving car. Google has made assurances that it will implement an ethics board to monitor its own AI developments (Shead, 2015).
AI technology has the promise to propel technology at a pace beyond human capabilities. We as humans need to eat, sleep and take breaks during the day and are not able to work on any one task every hour of every day. AI has no such limitations and can run virtual simulations and evaluate results much faster and much longer than people. The technology is already being used to power analytic engines at Google and other companies (MIT Technology Review, 2015). On the flip side of this, if machines get to the point that they are taking jobs away from people then we could see an unforeseen economic impact.
Google Project Loon Balloon Internet Technology Google’s Project Loon is an effort to create a network of balloons travelling at high altitudes that will be able to provide connectivity to remote areas and to provide service following disasters. These balloons will be placed in earth’s stratosphere where they will be maneuvered by changing their altitude depending on wind directions at different altitudes where wind speeds and directions change (Google.com, 2015). These devices will be able to provide coverage to an area the size of Rhode Island (Hof, 2015). These balloons can be networked to fill in areas of the world where there is no reliable coverage, which is about 90% of the earth’s surface. A big challenge to implementing balloon network challenges is that the components need to be able to withstand very harsh conditions that exist in very high altitudes including harsh winds and extremely cold temperatures (Kelion, 2015). To navigate the balloons, onboard valves need to be able to open and close to adjust altitude to ride the correct wind directions, allowing them to stay aloft as along as possible (Hof, 2015). The balloon material needs to be able to withstand the same environmental conditions for the same reasons. Aside from the technology itself, any object that is in the air will need to be tracked and identified on air traffic control systems to avoid becoming an air hazard for planes.
More testing of the materials to ensure that they can withstand the elements will be required. The testing so far has resulted in the balloons only being able to stay in flight for a few days. I think that using solar powered devices to provide heat to components at high altitudes could help keep critical sensors and devices to remain in operation for longer periods. Due to the fact that this type of technology has not been implemented before there is much that is being learned through each test. I realize this is a low-tech solution which makes this an interesting proposition, but I wonder if other technologies might be better suited for this type of deployment. In particular, I could see solar powered drones flying at that altitude and offering the same type of coverage.
Google’s Loon technology has the potential to bring internet coverage to a much broader audience which can certainly help educate and improve the quality of life for many who do not currently have connectivity. I do think that having Loon as a quickly deployable solution to help restore coverage in disaster stricken areas could greatly help the spread of information and speed up recovery efforts. The connectivity could give agencies like the Federal Emergency Management Agency (FEMA) visibility into disasters more quickly so the correct resources could be dispatched in a faster more efficient manner.
Google Nest Home Automation Technology Google’s Nest project develops products used for home automation. This technology allows homeowners to control different systems and sensors in their home, including thermostats, camera, fire alarms, lights and door locks (della Cava, 2015). The idea is to combine these sensors and systems in the home to add to the internet of things (IoT) and use big data analytics to determine the most efficient settings based on how people live (Marr, 2015). These devices have the potential to learn our behaviors and control the systems in our homes, which can be optimized to be more energy efficient.
Currently Google Nest home control devices cost more than standard thermostats and door lock so their adoption rates will be slow until the initial costs are reduced. Low income users and renters that could benefit from the technology the most are going to be less likely to adopt it due to the initial cost (Fitzpatrick, 2015). Additionally, there will be a slower adoption by those who are concerned that the devices could be used to spy on them. As with any internet device, there is always the possibility of a vulnerability existing that could allow a hacker, or even the government, take control of a camera or other device.
Some of the costs associated with upgrading to a Nest smart device may be able to be covered by local utility energy conservation rebates and subsidies (Marr, 2015). Education can help potential buyers understand that the potential savings in energy can help the device pay for itself over time. It is estimated that Nest technology users have saved nearly four billion kilowatt hours of energy over what they would have used by keeping thermostats set to the same temperature (della Cava, 2015). Users also need to be educated on how to configure networks to make them, and connected devices, less prone to hackers and outside control.
The use of internet connected devices and the ability to use big data analytics also allows consumers to apply technology to existing environmental control systems making them much smarter (Marr, 2015). This technology has the potential to reduce energy consumption and save consumers money over time. Any effort to reduce the use of fossil fuels and their effects on pollution and its contribution to global warming can only benefit society.
Project Wing Drone Technology Google’s project wing is their effort to develop a smart, remote controlled delivery system utilizing drones. The drones themselves are powered by electric motors that use propellers like a helicopter that allow the devices to be deployed without a runway (Ingraham, 2014). The system was original planned to be a system for delivering emergency automatic electric defibrillators (AED) to people experiencing heart a heart attack. Google’s primary application would be to deliver supplies in disaster stricken areas (Ingraham, 2014). There are also obvious applications around consumer product delivery.
Google faces a few challenges in deploying drone technology. One of the main concerns is how drone air traffic would be handled to ensure that these devices can be safely and easily deployed (Stone, 2015). Amazon is also developing similar technology and has already obtained a patent on its technology (POETER, 2015). A second concern is that currently, it is illegal for unmanned drones to be deployed (Reich, 2015).
To make sure that drones could be deployed safely, systems on the drones would need to be integrated with existing air traffic systems and contain systems that would allow them to avoid crashing into one another. At some point, Google would need to collaborate with Amazon, and other companies to define how drones would inter-operate and avoid conflicting paths (Terdiman, 2015). Much like with self-driving vehicles, legislation would need to be changed to strictly control how these types of devices could be safely deployed (Reich, 2015).
Drone technology has the potential to help get supplies to people in times of disaster. The survivors of hurricane Katrina could have benefited from this technology as desperately needed supplies could have been deployed quickly. Google’s Project Wing drones also have the potential to save lives by delivering AED devices and other emergency first aid to those in emergency situations. Finally, these devices can improve delivery times for consumer products purchased online. In contrast, drones could add a new level of traffic to urban areas causing congestion above already congested streets. It could also increase the possibility of malfunction or mid-air collisions that could put people on the grounds in harm’s way.
Conclusion
These are just some of the technologies that Google is working on that can be used to enhance quality of life and reduce the environment impact of travelling, delivery, heating and cooling. There are many other Google projects that have the potential to revolutionize medicine through Nano-technology and wearable medical devices and many others (Helft, 2014). While this technology has the potential to change lives across the world, there are security, environmental, legal, moral and ethical issues that need to be addressed. Just because a technology can be developed, it doesn’t mean that it should be developed. In history, Alfred Nobel invented Dynamite to use in construction and mining, but the technology quickly became a weapon of war (Lallanilla, 2013). The technology was useful, but also needed to be regulated to keep it out of the hands of those that would use the explosive maliciously. The same needs to be true for Google’s new technology. New technology that connects devices and sensors to the internet and that includes any processes that would replace human reasoning all aspects and uses of technology needs to be completely evaluated to make sure that it is secure, safe and can only be used for its intended purpose. New legislation will also need to be enacted to make sure that technology such as drones, balloons and self-driving cars don’t become hazards.

References
Bailey, R. (2014). The Moral Case for Self-Driving Cars. Reason.com. Retrieved 19 October 2015, from http://reason.com/archives/2014/07/28/the-moral-case-for-self-drivin/print

della Cava, M. (2015). Google self-driving car prototype meets the press. USA TODAY. Retrieved 19 October 2015, from http://www.usatoday.com/story/tech/2015/09/29/google-self-driving-car-prototype-meets-press/73042932/

della Cava, M. (2015). Google's Nest retools its signature thermostat. USA TODAY. Retrieved 19 October 2015, from http://www.usatoday.com/story/tech/2015/09/01/googles-nest-retools-its-signature-thermostat/71284384/

ExtremeTech,. (2015). Google x - News & Rumors | ExtremeTech. Retrieved 19 October 2015, from http://www.extremetech.com/tag/google-x

Fitzpatrick, J. (2015). Should You Buy Google’s Nest Learning Thermostat?. Howtogeek.com. Retrieved 27 October 2015, from http://www.howtogeek.com/213173/should-you-buy-googles-nest-learning-thermostat/

Gibbs, S. (2014). Google's self-driving car: How does it work and when can we drive one?. the Guardian. Retrieved 27 October 2015, from http://www.theguardian.com/technology/2014/may/28/google-self-driving-car-how-does-it-work

Google.com,. (2015). Loon for All – Project Loon – Google. Retrieved 19 October 2015, from http://www.google.com/loon/

Helft, M. (2014). Astro Teller: How Google X works. Fortune. Retrieved 19 October 2015, from http://fortune.com/2014/12/30/astro-teller-google-x/

Hof, R. (2015). Google's Project Loon Internet Balloons Coming To U.S. - Eventually. Forbes.com. Retrieved 19 October 2015, from http://www.forbes.com/sites/roberthof/2015/06/02/googles-project-loon-internet-balloons-coming-to-u-s-eventually/

Ingraham, N. (2014). Google's Project Wing is a secret, drone-based delivery system. The Verge. Retrieved 19 October 2015, from http://www.theverge.com/2014/8/28/6080369/googles-project-wing-is-a-secret-drone-based-delivery-system

Kelion, L. (2015). Google's Project Loon internet balloons to circle Earth - BBC News. BBC News. Retrieved 29 October 2015, from http://www.bbc.com/news/technology-34660205

Lallanilla, M. (2013). The Dark Side of the Nobel Prizes. LiveScience.com. Retrieved 1 November 2015, from http://www.livescience.com/40188-dark-history-alfred-nobel-prizes.html

Marr, B. (2015). Google's Nest: Big Data And The Internet Of Things In The Connected Home. Forbes.com. Retrieved 19 October 2015, from http://www.forbes.com/sites/bernardmarr/2015/08/05/googles-nest-big-data-and-the-internet-of-things-in-the-connected-home/

MIT Technology Review,. (2015). Google DeepMind Teaches Artificial Intelligence Machines to Read | MIT Technology Review. Retrieved 19 October 2015, from http://www.technologyreview.com/view/538616/google-deepmind-teaches-artificial-intelligence-machines-to-read/

POETER, D. (2015). Amazon Awarded Patent for Drone Delivery System. PCMAG. Retrieved 19 October 2015, from http://www.pcmag.com/article2/0,2817,2484058,00.asp

Reich, J. (2015). Google Quietly Teamed Up With NASA To Test Project Wing Drone Program. Tech Times. Retrieved 27 October 2015, from http://www.techtimes.com/articles/76392/20150813/google-quietly-teamed-up-nasa-test-project-wing-drone-program.htm

Research.google.com,. (2015). Research at Google. Retrieved 19 October 2015, from http://research.google.com/

Shead, S. (2015). Google DeepMind: What is it, how does it work and should you be scared?. Techworld. Retrieved 27 October 2015, from http://www.techworld.com/personal-tech/google-deepmind-what-is-it-how-it-works-should-you-be-scared-3615354/

Spector, A., Norvig, P., & Petrov, S. (2015). Google’s Hybrid Approach to Research. Research at Google. Retrieved 1 November 2015, from http://static.googleusercontent.com/media/research.google.com/en//pubs/archive/38149.pdf

Stone, B. (2015). Google Details New Project Loon Tech to Keep Its Internet Balloons Afloat. Bloomberg.com. Retrieved 27 October 2015, from http://www.bloomberg.com/news/articles/2015-05-29/google-details-new-project-loon-tech-to-keep-its-internet-balloons-afloat

Terdiman, D. (2015). Google's Project Wing Swoops Into Drone Air Traffic Control Conversation. Fast Company. Retrieved 20 October 2015, from http://www.fastcompany.com/3049186/tech-forecast/googles-project-wing-swoops-into-drone-air-traffic-control-conversation

Xavier, J. (2015). Corvette Chief Engineer on Why You Won’t See a Self-Driving Sports Car. Stanford Graduate School of Business. Retrieved 1 November 2015, from http://www.gsb.stanford.edu/insights/corvette-chief-engineer-why-you-wont-see-self-driving-sports-car…...

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