Artificial Intelligence - What Is The Trolley Problem?

 

Philippa Foot used the term "trolley problem" in 1967 to describe an ethical difficulty.

Artificial intelligence advancements in different domains have sparked ethical debates regarding how these systems' decision-making processes should be designed.

Of course, there is widespread worry about AI's capacity to assess ethical challenges and respect societal values.

An operator finds herself near a trolley track, standing next to a lever that determines whether the trolley will continue on its current path or go in a different direction, in this classic philosophical thought experiment.

Five people are standing on the track where the trolley is running, unable to get out of the path and certain to be murdered if the trolley continues on its current course.

On the opposite track, there is another person who will be killed if the operator pulls the lever.

The operator has the option of pulling the lever, killing one person while rescuing the other five, or doing nothing and allowing the other five to perish.

This is a typical problem between utilitarianism (activities should maximize the well-being of affected persons) and deontology (actions should maximize the well-being of affected individuals) (whether the action is right or wrong based on rules, as opposed to the consequences of the action).

With the development of artificial intelligence, the issue has arisen how we should teach robots to behave in scenarios that are perceived as inescapable realities, such as the Trolley Problem.

The Trolley Problem has been investigated with relation to artificial intelligence in fields such as primary health care, the operating room, security, self-driving automobiles, and weapons technology.

The subject has been studied most thoroughly in the context of self-driving automobiles, where regulations, guidelines, and norms have already been suggested or developed.

Because autonomous vehicles have already gone millions of kilometers in the United States, they face this difficulty.

The problem is made more urgent by the fact that a few self-driving car users have actually died while utilizing the technology.

Accidents have sparked even greater public discussion over the proper use of this technology.

Moral Machine is an online platform established by a team at the Massachusetts Institute of Technology to crowdsource responses to issues regarding how self-driving automobiles should prioritize lives.

The makers of The Moral Machine urge users to the website to guess what option a self-driving automobile would make in a variety of Trolley Problem-style problems.

Respondents must prioritize the lives of car passengers, pedestrians, humans and animals, people walking legally or illegally, and people of various fitness levels and socioeconomic status, among other variables.

When respondents are in a car, they almost always indicate that they would move to save their own lives.

It's possible that crowd-sourced solutions aren't the best method to solve Trolley Problem problems.

Trading a pedestrian life for a vehicle passenger's life, for example, may be seen as arbitrary and unjust.

The aggregated solutions currently do not seem to represent simple utilitarian calculations that maximize lives saved or favor one sort of life over another.

It's unclear who will get to select how AI will be programmed and who will be held responsible if AI systems fail.

This obligation might be assigned to policymakers, the corporation that develops the technology, or the people who end up utilizing it.

Each of these factors has its own set of ramifications that must be handled.

The Trolley Problem's usefulness in resolving AI quandaries is not widely accepted.

The Trolley Problem is dismissed by some artificial intelligence and ethics academics as a helpful thinking exercise.

Their arguments are usually based on the notion of trade-offs between different lifestyles.

They claim that the Trolley Problem lends credence to the idea that these trade-offs (as well as autonomous vehicle disasters) are unavoidable.

Instead than concentrating on the best methods to avoid a dilemma like the trolley issue, policymakers and programmers should instead concentrate on the best ways to react to the different circumstances.

~ Jai Krishna Ponnappan

Find Jai on Twitter | LinkedIn | Instagram

You may also want to read more about Artificial Intelligence here.

See also: 

Accidents and Risk Assessment; Air Traffic Control, AI and; Algorithmic Bias and Error; Autonomous Weapons Systems, Ethics of; Driverless Cars and Trucks; Moral Turing Test; Robot Ethics.

References And Further Reading

Cadigan, Pat. 2018. AI and the Trolley Problem. New York: Tor.

Etzioni, Amitai, and Oren Etzioni. 2017. “Incorporating Ethics into Artificial Intelligence.” Journal of Ethics 21: 403–18.

Goodall, Noah. 2014. “Ethical Decision Making during Automated Vehicle Crashes.” Transportation Research Record: Journal of the Transportation Research Board 2424: 58–65.

Moolayil, Amar Kumar. 2018. “The Modern Trolley Problem: Ethical and Economically Sound Liability Schemes for Autonomous Vehicles.” Case Western Reserve Journal of Law, Technology & the Internet 9, no. 1: 1–32.

Artificial Intelligence - What Is The Liability Of Self-Driving Vehicles?

 

Driverless cars may function completely or partly without the assistance of a human driver.

Driverless automobiles, like other AI products, confront difficulties with liability, responsibility, data protection, and customer privacy.

Driverless cars have the potential to eliminate human carelessness while also providing safe transportation for passengers.

They have been engaged in mishaps despite their potential.

The Autopilot software on a Tesla SUV may have failed to notice a huge vehicle crossing the highway in a well-publicized 2016 accident.

A Tesla Autopilot may have been involved in the death of a 49-year-old woman in 2018.

A class action lawsuit was filed against Tesla as a result of these occurrences, which the corporation resolved out of court.

Additional worries about autonomous cars have arisen as a result of bias and racial prejudice in machine vision and face recognition.

Current driverless cars may be better at spotting people with lighter skin, according to Georgia Institute of Technology researchers.

Product liability provides some much-needed solutions to such problems.

The Consumer Protection Act of 1987 governs product liability claims in the United Kingdom (CPA).

This act enacts the European Union's (EU) Product Liability Directive 85/374/EEC, which holds manufacturers liable for product malfunctions, i.e., items that are not as safe as they should be when bought.

This contrasts with U.S. law addressing product liability, which is fragmented and largely controlled by common law and a succession of state acts.

The Uniform Commercial Code (UCC) offers remedies where a product fails to fulfill stated statements, is not merchantable, or is inappropriate for its specific use.

In general, manufacturers are held accountable for injuries caused by their faulty goods, and this responsibility may be handled in terms of negligence or strict liability.

A defect in this situation could be a manufacturer defect, where the driverless vehicle does not satisfy the manufacturer’s specifications and standards; a design defect, which can result when an alternative design would have prevented an acci dent; or a warning defect, where there is a failure to provide enough warning as regards to a driverless car’s operations.

To evaluate product responsibility, the five stages of automation specified by the Society of Automotive Engineers (SAE) International should be taken into account: Level 0, full control of a vehicle by a driver; Level 1, a human driver assisted by an automated system; Level 2, an automated system partially conduct ing the driving while a human driver monitors the environment and performs most of the driving; Level 3, an automated system does the driving and monitor ing of the environment, but the human driver takes back control when signaled; Level 4, the driverless vehicle conducts driving and monitors the environment but is restricted in certain environment; and Level 5, a driverless vehicle without any restrictions does everything a human driver would.

In Levels 1–3 that involve human-machine interaction, where it is discovered that the driverless vehicle did not communicate or send out a signal to the human driver or that the autopilot software did not work, the manufacturer will be liable based on product liability.

At Level 4 and Level 5, liability for defective product will fully apply.

Manufacturers have a duty of care to ensure that any driverless vehicle they manufacture is safe when used in any foreseeable manner.

Failure to exercise this duty will make them liable for negligence.

In some other cases, even when manufacturers have exercised all reasonable care, they will still be liable for unintended defects as per the strict liability principle.

The liability for the driver, especially in Levels 1–3, could be based on tort principles, too.

The requirement of article 8 of the 1949 Vienna Convention on Road Traffic, which states that “[e]very vehicle or combination of vehicles proceeding as a unit shall have a driver,” may not be fulfilled in cases where a vehicle is fully automated.

In some U.S. states, namely, Nevada and Florida, the word driver has been changed to controller, and the latter means any person who causes the autonomous technology to engage; the person must not necessarily be present in the vehicle.

A driver or controller becomes responsible if it is proved that the obligation of reasonable care was not performed by the driver or controller or they were negligent in the observance of this duty.

In certain other cases, victims will only be reimbursed by their own insurance companies under no-fault responsibility.

Victims may also base their claims for damages on the strict responsibility concept without having to present proof of the driver’s fault.

In this situation, the driver may demand that the manufacturer be joined in a lawsuit for damages if the driver or the controller feels that the accident was the consequence of a flaw in the product.

In any case, proof of the driver's or controller's negligence will reduce the manufacturer's liability.

Third parties may sue manufacturers directly for injuries caused by faulty items under product liability.

According to MacPherson v. Buick Motor Co. (1916), where the court found that an automobile manufacturer's duty for a faulty product goes beyond the initial consumer, there is no privity of contract between the victim and the maker.

The question of product liability for self-driving vehicles is complex.

The transition from manual to smart automated control transfers responsibility from the driver to the manufacturer.

The complexity of driving modes, as well as the interaction between the human operator and the artificial agent, is one of the primary challenges concerning accident responsibility.

In the United States, the law of motor vehicle product liability relating to flaws in self-driving cars is still in its infancy.

While the Department of Transportation and, especially, the National Highway Traffic Safety Administration give some basic recommendations on automation in driverless vehicles, Congress has yet to adopt self-driving car law.

In the United Kingdom, the Automated and Electric Cars Act of 2018 makes insurers accountable by default for accidents using automated vehicles that result in death, bodily injury, or property damage, providing the vehicles were in self-driving mode and insured at the time of the accident.

~ Jai Krishna Ponnappan

You may also want to read more about Artificial Intelligence here.

See also: 

Accidents and Risk Assessment; Product Liability and AI; Trolley Problem.

Further Reading:

Geistfeld. Mark A. 2017. “A Roadmap for Autonomous Vehicles: State Tort Liability, Automobile Insurance, and Federal Safety Regulation.” California Law Review 105: 1611–94.

Hevelke, Alexander, and Julian Nida-Rümelin. 2015. “Responsibility for Crashes of Autonomous Vehicles: An Ethical Analysis.” Science and Engineering Ethics 21, no. 3 (June): 619–30.

Karanasiou, Argyro P., and Dimitris A. Pinotsis. 2017. “Towards a Legal Definition of Machine Intelligence: The Argument for Artificial Personhood in the Age of Deep Learning.” In ICAIL ’17: Proceedings of the 16th edition of the International Conference on Artificial Intelligence and Law, edited by Jeroen Keppens and Guido Governatori, 119–28. New York: Association for Computing Machinery.

Luetge, Christoph. 2017. “The German Ethics Code for Automated and Connected Driving.” Philosophy & Technology 30 (September): 547–58.

Rabin, Robert L., and Kenneth S. Abraham. 2019. “Automated Vehicles and Manufacturer Responsibility for Accidents: A New Legal Regime for a New Era.” Virginia Law Review 105, no. 1 (March): 127–71.

Wilson, Benjamin, Judy Hoffman, and Jamie Morgenstern. 2019. “Predictive Inequity in Object Detection.” https://arxiv.org/abs/1902.11097.

Artificial Intelligence - Who Is Mark Tilden?

 

Mark Tilden(1961–) is a biomorphic robot freelance designer from Canada.

A number of his robots are sold as toys.

Others have appeared in television and cinema as props.

Tilden is well-known for his opposition to the notion that strong artificial intelligence is required for complicated robots.

Tilden is a forerunner in the field of BEAM robotics (biology, electronics, aesthetics, and mechanics).

To replicate biological neurons, BEAM robots use analog circuits and systems, as well as continuously varying signals, rather as digital electronics and microprocessors.

Biomorphic robots are programmed to change their gaits in order to save energy.

When such robots come into impediments or changes in the underlying terrain, they are knocked out of their lowest energy condition, forcing them to adapt to a new walking pattern.

The mechanics of the underlying machine rely heavily on self-adaptation.

After failing to develop a traditional electronic robot butler in the late 1980s, Tilden resorted to BEAM type robots.

The robot could barely vacuum floors after being programmed with Isaac Asimov's Three Laws of Robotics.

After hearing MIT roboticist Rodney Brooks speak at Waterloo University on the advantages of basic sensorimotor, stimulus-response robotics versus computationally complex mobile devices, Tilden completely abandoned the project.

Til den left Brooks' lecture questioning if dependable robots might be built without the use of computer processors or artificial intelligence.

Rather than having the intelligence written into the robot's programming, Til den hypothesized that the intelligence may arise from the robot's operating environment, as well as the emergent features that resulted from that world.

Tilden studied and developed a variety of unusual analog robots at the Los Alamos National Laboratory in New Mexico, employing fast prototyping and off-the-shelf and cannibalized components.

Los Alamos was looking for robots that could operate in unstructured, unpredictable, and possibly hazardous conditions.

Tilden built almost a hundred robot prototypes.

His SATBOT autonomous spaceship prototype could align itself with the Earth's magnetic field on its own.

He built fifty insectoid robots capable of creeping through minefields and identifying explosive devices for the Marine Corps Base Quantico.

A robot known as a "aggressive ashtray" spits water at smokers.

A "solar spinner" was used to clean the windows.

The actions of an ant were reproduced by a biomorph made from five broken Sony Walkmans.

Tilden started building Living Machines powered by solar cells at Los Alamos.

These machines ran at extremely sluggish rates due to their energy source, but they were dependable and efficient for lengthy periods of time, often more than a year.

Tilden's first robot designs were based on thermodynamic conduit engines, namely tiny and efficient solar engines that could fire single neurons.

Rather than the workings of their brains, his "nervous net" neurons controlled the rhythms and patterns of motion in robot bodies.

Tilden's idea was to maximize the amount of patterns conceivable while using the fewest number of implanted transistors feasible.

He learned that with just twelve transistors, he could create six different movement patterns.

Tilden might replicate hopping, leaping, running, sitting, crawling, and a variety of other patterns of behavior by folding the six patterns into a figure eight in a symmetrical robot chassis.

Since then, Tilden has been a proponent of a new set of robot principles for such survivalist wild automata.

Tilden's Laws of Robotics say that (1) a robot must safeguard its survival at all costs; (2) a robot must get and keep access to its own power source; and (3) a robot must always seek out better power sources.

Tilden thinks that wild robots will be used to rehabilitate ecosystems that have been harmed by humans.

Tilden had another breakthrough when he introduced very inexpensive robots as toys for the general public and robot aficionados.

He wanted his robots to be in the hands of as many people as possible, so that hackers, hobbyists, and members of different maker communities could reprogramme and modify them.

Tilden designed the toys in such a way that they could be dismantled and analyzed.

They might be hacked in a basic way.

Everything is color-coded and labeled, and all of the wires have gold-plated contacts that can be ripped apart.

Tilden is presently working with WowWee Toys in Hong Kong on consumer-oriented entertainment robots:

• B.I.O. Bugs, Constructobots, G.I. Joe Hoverstrike, Robosapien, Roboraptor, Robopet, Roborep tile, Roboquad, Roboboa, Femisapien, and Joebot are all popular WowWee robot toys.
• The Roboquad was designed for the Jet Propulsion Laboratory's (JPL) Mars exploration program.
• Tilden is also the developer of the Roomscooper cleaning robot.

WowWee Toys sold almost three million of Tilden's robot designs by 2005.

Tilden made his first robotic doll when he was three years old.

At the age of six, he built a Meccano suit of armor for his cat.

At the University of Waterloo, he majored in Systems Engineering and Mathematics.

Tilden is presently working on OpenCog and OpenCog Prime alongside artificial intelligence pioneer Ben Goertzel.

OpenCog is a worldwide initiative supported by the Hong Kong government that aims to develop an open-source emergent artificial general intelligence framework as well as a common architecture for embodied robotic and virtual cognition.

Dozens of IT businesses across the globe are already using OpenCog components.

Tilden has worked on a variety of films and television series as a technical adviser or robot designer, including Lara Croft: Tomb Raider (2001), The 40-Year-Old Virgin (2005), Paul Blart Mall Cop (2009), and X-Men: The Last Stand (2006).

In the Big Bang Theory (2007–2019), his robots are often displayed on the bookshelves of Sheldon's apartment.

~ Jai Krishna Ponnappan

Find Jai on Twitter | LinkedIn | Instagram

You may also want to read more about Artificial Intelligence here.

See also: 

Brooks, Rodney; Embodiment, AI and.

References And Further Reading

Frigo, Janette R., and Mark W. Tilden. 1995. “SATBOT I: Prototype of a Biomorphic Autonomous Spacecraft.” Mobile Robotics, 66–75.

Hapgood, Fred. 1994. “Chaotic Robots.” Wired, September 1, 1994. https://www.wired.com/1994/09/tilden/.

Hasslacher, Brosl, and Mark W. Tilden. 1995. “Living Machines.” Robotics and Autonomous Systems 15, no. 1–2: 143–69.

Marsh, Thomas. 2010. “The Evolution of a Roboticist: Mark Tilden.” Robot Magazine, December 7, 2010. http://www.botmag.com/the-evolution-of-a-roboticist-mark-tilden.

Menzel, Peter, and Faith D’Aluisio. 2000. “Biobots.” Discover Magazine, September 1, 2000. https://www.discovermagazine.com/technology/biobots.

Rietman, Edward A., Mark W. Tilden, and Manor Askenazi. 2003. “Analog Computation with Rings of Quasiperiodic Oscillators: The Microdynamics of Cognition in Living Machines.” Robotics and Autonomous Systems 45, no. 3–4: 249–63.

Samans, James. 2005. The Robosapiens Companion: Tips, Tricks, and Hacks. New York: Apress.

Artificial Intelligence - What Is The Stop Killer Robots Campaign?

 

The Campaign to Stop Killer Robots is a non-profit organization devoted to mobilize and campaign against the development and deployment of deadly autonomous weapon systems (LAWS).

The campaign's main issue is that armed robots making life-or-death decisions undercut legal and ethical restraints on violence in human conflicts.

Advocates for LAWS argue that these technologies are compatible with current weapons and regulations, such as cruise missiles that are planned and fired by humans to hunt out and kill a specific target.

Advocates also say that robots are completely reliant on people, that they are bound by their design and must perform the behaviors that have been assigned to them, and that with appropriate monitoring, they may save lives by substituting humans in hazardous situations.

The Campaign to Stop Killer Robots dismisses responsible usage as a viable option, stating fears that the development of LAWS could result in a new arms race.

The advertisement underlines the danger of losing human control over the use of lethal force in situations when armed robots identify and remove a threat before human intervention is feasible.

Human Rights Watch, an international nongovernmental organization (NGO) that promotes fundamental human rights and investigates violations of those rights, organized and managed the campaign, which was officially launched on April 22, 2013, in London, England.

Many member groups make up the Campaign to Stop Killer Robots, including the International Committee for Robot Arms Control and Amnesty International.

A steering group and a worldwide coordinator are in charge of the campaign's leadership.

As of 2018, the steering committee consists of eleven non-governmental organizations.

Mary Wareham, who formerly headed international efforts to ban land mines and cluster bombs, is the campaign's worldwide coordinator.

Efforts to ban armed robots, like those to ban land mines and cluster bombs, concentrate on their potential to inflict needless suffering and indiscriminate damage to humans.

The United Nations Convention on Certain Conventional Weapons (CCW), which originally went into force in 1983, coordinates the worldwide ban of weapons.

Because the CCW has yet to agree on a ban on armed robots, and because the CCW lacks any mechanism for enforcing agreed-upon restrictions, the Campaign to Stop Killer Robots calls for the inclusion of LAWS in the CCW.

The Campaign to Stop Killer Robots also promotes the adoption of new international treaties to implement more preemptive restrictions.

The Campaign to Stop Killer Robots offers tools for educating and mobilizing the public, including multimedia databases, campaign reports, and a mailing list, in addition to lobbying governing authorities for treaty and convention prohibitions.

The Campaign also seeks the participation of technological businesses, requesting that they refuse to participate in the creation of LAWS on their own will.

The @BanKillerRobots account on Twitter is where the Campaign keeps track of and broadcasts the names of companies that have pledged not to engage in the creation or marketing of intelligent weapons.

~ Jai Krishna Ponnappan

You may also want to read more about Artificial Intelligence here.

See also: 

Autonomous Weapons Systems, Ethics of; Battlefield AI and Robotics; Lethal Autonomous Weapons Systems.

Further Reading

Baum, Seth. 2015. “Stopping Killer Robots and Other Future Threats.” Bulletin of the Atomic Scientists, February 22, 2015. https://thebulletin.org/2015/02/stopping-killer-robots-and-other-future-threats/.

Campaign to Stop Killer Robots. 2020. https://www.stopkillerrobots.org/.

Carpenter, Charli. 2016. “Rethinking the Political / -Science- / Fiction Nexus: Global Policy Making and the Campaign to Stop Killer Robots.” Perspectives on Politics 14, no. 1 (March): 53–69.

Docherty, Bonnie. 2012. Losing Humanity: The Case Against Killer Robots. New York: Human Rights Watch.

Garcia, Denise. 2015. “Killer Robots: Why the US Should Lead the Ban.” Global Policy6, no. 1 (February): 57–63.

AI - Smart Homes And Smart Cities.

 

Projects to develop the infrastructure for smart cities and houses are involving public authorities, professionals, businessmen, and residents all around the world.

These smart cities and houses make use of information and communication technology (ICT) to enhance quality of life, local and regional economies, urban planning and transportation, and government.

Urban informatics is a new area that gathers data, analyzes patterns and trends, and utilizes the information to implement new ICT in smart cities.

Data may be gathered from a number of different sources.

Surveillance cameras, smart cards, internet of things sensor networks, smart phones, RFID tags, and smart meters are just a few examples.

In real time, any kind of data may be captured.

Passenger occupancy and flow may be used to obtain data on mass transit utilization.

Road sensors can count cars on the road or in parking lots.

They may also use urban machine vision technologies to determine individual wait times for local government services.

From public thoroughfares and sidewalks, license plate numbers and people's faces may be identified and documented.

Tickets may be issued, and statistics on crime can be gathered.

The information gathered in this manner may be compared to other big datasets on neighborhood income, racial and ethnic mix, utility reliability statistics, and air and water quality indices.

Artificial intelligence (AI) may be used to build or improve city infrastructure.

Stop signal frequencies at crossings are adjusted and optimized based on data acquired regarding traffic movements.

This is known as intelligent traffic signaling, and it has been found to cut travel and wait times, as well as fuel consumption, significantly.

Smart parking structures assist cars in quickly locating available parking spaces.

Law enforcement is using license plate identification and face recognition technologies to locate suspects and witnesses at crime scenes.

Shotspotter, a business that triangulates the position of gunshots using a sensor network placed in special streetlights, tracked and informed police agencies to over 75,000 bullets fired in 2018.

Information on traffic and pedestrian deaths is also being mined via big data initiatives.

Vision Zero is a global highway safety initiative that aspires to decrease road fatalities to zero.

Data analysis using algorithms has resulted in road safety efforts as well as road redesign that has saved lives.

Cities have also been able to respond more swiftly to severe weather occurrences because to ubiquitous sensor technology.

In Seattle, for example, conventional radar data is combined with RainWatch, a network of rain gauges.

Residents get warnings from the system, and maintenance staff are alerted to possible problem places.

Transport interconnection enabling completely autonomous autos is one long-term aim for smart cities.

At best, today's autonomous cars can monitor their surroundings to make judgments and avoid crashes with other vehicles and numerous road hazards.

However, cars that connect with one another in several directions are likely to create fully autonomous driving systems.

Collisions are not only averted, but also prevented in these systems.

Smart cities are often mentioned in conjunction with smart economy initiatives and foreign investment development by planners.

Data-driven entrepreneurial innovation, as well as productivity analyses and evaluation, might be indicators of sensible economic initiatives.

Some smart towns want to emulate Silicon Valley's success.

Neom, Saudi Arabia, is one such project.

It is a proposed megacity city that is expected to cost half a trillion dollars to build.

Artificial intelligence is seen as the new oil in the city's ambitions, despite sponsorship by Saudi Aramco, the state-owned petroleum giant.

Everything will be controlled by interconnected computer equipment and future artificial intelligence decision-making, from home technology to transportation networks and electronic medical record distribution.

One of Saudi Arabia's most significant cultural activities—monitoring the density and pace of pilgrims around the Kaaba in Mecca—has already been entrusted to AI vision technologies.

The AI is intended to avert a disaster on the scale of the 2015 Mina Stampede, which claimed the lives of 2,000 pilgrims.

The use of highly data-driven and targeted public services is another trademark of smart city programs.

Information-driven agencies are frequently referred to as "smart" or "e-government" when they work together.

Open data projects to encourage openness and shared engagement in local decision-making might be part of smart governance.

Local governments will collaborate with contractors to develop smart utility networks for the provision of electricity, telecommunications, and the internet.

Waste bins are linked to the global positioning system and cloud servers, alerting vehicles when garbage is ready for pickup, allowing for smart waste management and recycling initiatives in Barcelona.

Lamp poles have been converted into community wi-fi hotspots or mesh networks in certain areas to provide pedestrians with dynamic lighting safety.

Forest City in Malaysia, Eko Atlantic in Nigeria, Hope City in Ghana, Kigamboni New City in Tanzania, and Diamniadio Lake City in Senegal are among the high-tech centres proposed or under development.

Artificial intelligence is predicted to be the brain of the smart city in the future.

Artificial intelligence will personalize city experiences to match the demands of specific inhabitants or tourists.

Through customized glasses or heads-up displays, augmented systems may give virtual signs or navigational information.

Based on previous use and location data, intelligent smartphone agents are already capable of predicting user movements.

Artificial intelligence technologies are used in smart homes in a similar way.

Google Home and other smart hubs now integrate with over 5,000 different types of smart gadgets sold by 400 firms to create intelligent environments in people's homes.

Amazon Echo is Google Home's main rival.

These kinds of technologies can regulate heating, ventilation, and air conditioning, as well as lighting and security, as well as household products like smart pet feeders.

In the early 2000s, game-changing developments in home robotics led to widespread consumer acceptance of iRobot's Roomba vacuum cleaner.

Obsolescence, proprietary protocols, fragmented platforms and interoperability issues, and unequal technological standards have all plagued such systems in the past.

Machine learning is being pushed forward by smart houses.

Smart technology' analytical and predictive capabilities are generally regarded as the backbone of one of the most rapidly developing and disruptive commercial sectors: home automation.

To function properly, the smarter connected home of the future needs collect fresh data on a regular basis in order to develop.

Smart houses continually monitor the interior environment and use aggregated past data to establish settings and functionalities in buildings with smart components installed.

Smart houses may one day anticipate their owners' requirements, such as automatically changing blinds as the sun and clouds move across the sky.

A smart house may produce a cup of coffee at precisely the correct time, order Chinese takeout, or play music based on the resident's mood as detected by emotion detectors.

Pervasive, sophisticated technologies are used in smart city and household AI systems.

The benefits of smart cities are many.

Smart cities pique people's curiosity because of its promise for increased efficiency and convenience.

It's enticing to live in a city that anticipates and easily fulfills personal wants.

Smart cities, however, are not without their detractors.

Smart havens, if left uncontrolled, have the ability to cause major privacy invasion via continuous video recording and microphones.

Google contractors might listen to recordings of exchanges with users of its famous Google Assistant artificial intelligence system, according to reports in 2019.

The influence of smart cities and households on the environment is yet unknown.

Biodiversity considerations are often ignored in smart city ideas.

Critical habitat is routinely destroyed in order to create space for the new cities that tech entrepreneurs and government officials desire.

Conventional fossil-fuel transportation methods continue to reign supreme in smart cities.

The future viability of smart homes is likewise up in the air.

A recent research in Finland found that improved metering and consumption monitoring did not successfully cut smart home power use.

In reality, numerous smart cities that were built from the ground up are now almost completely empty.

Many years after their initial construction, China's so-called ghost cities, such as Ordos Kangbashi, have attained occupancy levels of one-third of all housing units.

Despite direct, automated vacuum waste collection tubes in individual apartments and building elevators timed to the arrival of residents' automobiles, Songdo, Korea, an early "city in a box," has not lived up to promises.

Smart cities are often portrayed as impersonal, elitist, and costly, which is the polar opposite of what the creators intended.

Songdo exemplifies the smart city trend in many aspects, with its underpinning structure of ubiquitous computing technologies that power everything from transportation systems to social networking channels.

The unrivaled integration and synchronization of services is made possible by the coordination of all devices.

As a result, by turning the city into an electronic panopticon or surveillance state for observing and controlling residents, the city simultaneously weakens the protective advantages of anonymity in public settings.

Authorities studying smart city infrastructures are now fully aware of the computational biases of proactive and predictive policing.

~ Jai Krishna Ponnappan

Find Jai on Twitter | LinkedIn | Instagram

You may also want to read more about Artificial Intelligence here.

See also: 

Biometric Privacy and Security; Biometric Technology; Driverless Cars and Trucks; Intelligent Transportation; Smart Hotel Rooms.

References & Further Reading:

Albino, Vito, Umberto Berardi, and Rosa Maria Dangelico. 2015. “Smart Cities: Definitions, Dimensions, Performance, and Initiatives.” Journal of Urban Technology 22, no. 1: 3–21.

Batty, Michael, et al. 2012. “Smart Cities of the Future.” European Physical Journal Special Topics 214, no. 1: 481–518.

Friedman, Avi. 2018. Smart Homes and Communities. Mulgrave, Victoria, Australia: Images Publishing.

Miller, Michael. 2015. The Internet of Things: How Smart TVs, Smart Cars, Smart Homes, and Smart Cities Are Changing the World. Indianapolis: Que.

Shepard, Mark. 2011. Sentient City: Ubiquitous Computing, Architecture, and the Future of Urban Space. New York: Architectural League of New York.

Townsend, Antony. 2013. Smart Cities: Big Data, Civic Hackers, and the Quest for a New Utopia. New York: W. W. Norton & Company.

Artificial Intelligence - Who Is Hiroshi Ishiguro (1963–)?

  

Hiroshi Ishiguro is a well-known engineer who is most known for his life-like humanoid robots.

He thinks that the present information culture will eventually develop into a world populated by robot caregivers or helpmates.

Ishiguro also expects that studying artificial people would help us better understand how humans are conditioned to read and comprehend the actions and expressions of their own species.

Ishiguro seeks to explain concepts like relationship authenticity, autonomy, creativity, imitation, reciprocity, and robot ethics in terms of cognitive science.

Ishiguro's study aims to produce robots that are uncannily identical to humans in look and behavior.

He thinks that his robots will assist us in comprehending what it is to be human.

Sonzaikan is the Japanese name for this sense of a human's substantial presence, or spirit.

Success, according to Ishiguro, may be measured and evaluated in two ways.

The first is what he refers to as the complete Turing Test, in which an android passes if 70% of human spectators are unaware that they are seeing a robot until at least two seconds have passed.

The second metric for success, he claims, is the length of time a human stays actively engaged with a robot before discovering that the robot's cooperative eye tracking does not reflect true thinking.

Robovie was one of Ishiguro's earliest robots, launched in 2000.

Ishiguro intended to make a robot that didn't appear like a machine or a pet, but might be mistaken for a friend in everyday life.

Robovie may not seem to be human, but it can perform a variety of innovative human-like motions and interactive activities.

Eye contact, staring at items, pointing at things, nodding, swinging and folding arms, shaking hands, and saying hello and goodbye are all possible with Robovie.

Robo Doll was extensively featured in Japanese media, and Ishiguro was persuaded that the robot's look, engagement, and conversation were vital to deeper, more nuanced connections between robots and humans.

In 2003, Ishiguro debuted Actroid to the general public for the first time.

Sanrio's Kokoro animatronics division has begun manufacturing Actroid, an autonomous robot controlled by AI software developed at Osaka University's Intelligent Robotics Laboratory.

Actroid has a feminine look (in science fiction terms, a "gynoid") with skin constructed of incredibly realistic silicone.

Internal sensors and quiet air actuators at 47 points of physical articulation allow the robot to replicate human movement, breathing, and blinking, and it can even speak.

Movement is done by sensor processing, data files carrying key val ues for degrees of freedom in movement of limbs and joints.

Five to seven degrees of freedom are typical for robot arms.

Arms, legs, torso, and neck of humanoid robots may have thirty or more degrees of freedom.

Programmers create Actroid scenarios in four steps: (1) collect recognition data from sensors activated by contact, (2) choose a motion module, (3) execute a specified series of movements and play an audio file, and (4) return to step 1.

Experiments utilizing irregular random or contingent reactions to human context hints have been shown to be helpful in holding the human subject's attention, but they are made much more effective when planned scenarios are included.

Motion modules are written in XML, a text-based markup language that is simple enough for even inexperienced programmers to understand.

Ishiguro debuted Repliee variants of the Actroid in 2005, which were supposed to be indistinguishable from a human female on first glance.

Repliee Q1Expo is an android replica of Ayako Fujii, a genuine Japanese newscaster.

Repliee androids are interactive; they can use voice recognition software to comprehend human conversations, answer verbally, maintain eye contact, and react quickly to human touch.

This is made possible by a sensor network made up of infrared motion detectors, cameras, microphones, identification tag readers, and floor sensors that is distributed and ubiquitous.

Artificial intelligence is used by the robot to assess whether the human is contacting the robot gently or aggressively.

Ishiguro also debuted Repliee R1, a kid version of the robot that looks identical to his then four-year-old daughter.

Actroids have recently been proven to be capable of imitating human limb and joint movement by observing and duplicating the movements.

Because much of the computer gear that runs the artificial intelligence program is external to the robot, it is not capable of actual movement.

Self-reports of human volunteers' sentiments and moods are captured when robots perform activities in research done at Ishiguro's lab.

The Actroid elicits a wide spectrum of emotions, from curiosity to disgust, acceptance to terror.

Ishiguro's research colleagues have also benefited from real-time neuroimaging of human volunteers in order to better understand how human brains are stimulated in human-android interactions.

As a result, Actroid serves as a testbed for determining why particular nonhuman agent acts fail to elicit the required cognitive reactions in humans.

The Geminoid robots were created in response to the fact that artificial intelligence lags far behind robotics when it comes to developing realistic interactions between humans and androids.

Ishiguro, in particular, admitted that it would be several years before a computer could have a lengthy, intensive spoken discussion with a person.

The Geminoid HI-1, which debuted in 2006, is a teleoperated (rather than totally autonomous) robot that looks similar to Ishiguro.

The name "gemininoid" is derived from the Latin word "twin." Hand fidgeting, blinking, and motions similar with human respiration are all possible for Geminoid.

Motion-capture technology is used to operate the android, which mimics Ishiguro's face and body motions.

The robot can imitate its creator's voice and communicate in a human-like manner.

Ishiguro plans to utilize the robot to teach students through remote telepresence one day.

When he is teleoperating the robot, he has observed that the sensation of immersion is so strong that his brain is fooled into producing phantom perceptions of actual contact when the android is poked.

The Geminoid-DK is a mechanical doppelgänger of Danish psychology professor Henrik Schärfe, launched in 2011.

While some viewers find the Geminoid's look unsettling, many others do not and simply communicate with the robot in a normal way.

In 2010, the Telenoid R1 was introduced as a teleoperated android robot.

Telenoid is 30 inches tall and amorphous, with just a passing resemblance to a human form.

The robot's objective is to transmit a human voice and gestures to a spectator who may use it as a communication or videoconferencing tool.

The Telenoid, like the other robots in Ishiguro's lab, looks to be alive: it simulates breathing and speech gestures and blinks.

However, in order to stimulate creativity, the design limits the amount of features.

In this manner, the Telenoid is analogous to a tangible, real-world avatar.

Its goal is to make more intimate, human-like interactions possible using telecommunications technology.

Ishiguro suggests that the robot might one day serve as a suitable stand-in for a teacher or partner who is otherwise only accessible from afar.

The Elfoid, a tiny version of the robot, can be grasped with one hand and carried in a pocket.

The autonomous persocom dolls that replace smart phones and other electronics in the immensely famous manga series Chobits foreshadowed the Actroid and Telenoid.

Ishiguro is a professor of systems innovation and the director of Osaka University's Intelligent Robotics Laboratory.

He's also a group leader at Kansai Science City's Advanced Telecommunications Research Institute (ATR) and a cofounder of the tech-transfer startup Vstone Ltd.

He thinks that future commercial enterprises will profit from the success of teleoperated robots in order to fund the continued development of his autonomous robots.

Erica, a humanoid robot that became a Japanese television news presenter in 2018, is his most recent creation.

Ishiguro studied oil painting extensively as a young man, pondering how to depict human resemblance on canvas while he worked.

In Hanao Mori's computer science lab at Yamanashi University, he got enthralled with robots.

At Osaka University, Ishiguro pursued his PhD in engineering under computer vision and image recognition pioneer Saburo Tsuji.

At studies done in Tsuji’s lab, he worked on mobile robots capable of SLAM— simultaneous mapping and navigation using panoramic and omni-directional video cameras.

This work led to his doctoral dissertation, which focused on tracking a human subject using active camera control and panning to acquire complete 360-degree views of the surroundings.

Ishiguro believed that his technology and applications may be utilized to provide a meaningful internal map of an interacting robot's surroundings.

His dissertation was rejected by the first reviewer of an article based on it.

Fine arts and technology, according to Ishiguro, are inexorably linked; art inspires new technologies, while technology enables for the creation and duplication of art.

Ishiguro has recently brought his robots to Seinendan, a theatre company founded by Oriza Hirata, in order to put what he's learned about human-robot communication into practice.

Ishiguro's field of cognitive science and AI, which he calls android science, has precedents in Disneyland's "Great Moments with Mr.

Lincoln" robotics animation show and the fictitious robot replacements described in the Bruce Willis film Surrogates (2009).

In the Willis film, Ishiguro has a cameo appearance.

~ Jai Krishna Ponnappan

You may also want to read more about Artificial Intelligence here.

See also: 

Caregiver Robots; Nonhuman Rights and Personhood.

Further Reading:

Guizzo, Erico. 2010. “The Man Who Made a Copy of Himself.” IEEE Spectrum 47, no. 4 (April): 44–56.

Ishiguro, Hiroshi, and Fabio Dalla Libera, eds. 2018. Geminoid Studies: Science and Technologies for Humanlike Teleoperated Androids. New York: Springer.

Ishiguro, Hiroshi, and Shuichi Nishio. 2007. “Building Artificial Humans to Understand Humans.” Journal of Artificial Organs 10, no. 3: 133–42.

Ishiguro, Hiroshi, Tetsuo Ono, Michita Imai, Takeshi Maeda, Takayuki Kanda, and Ryohei Nakatsu. 2001. “Robovie: An Interactive Humanoid Robot.” International Journal of Industrial Robotics 28, no. 6: 498–503.

Kahn, Peter H., Jr., Hiroshi Ishiguro, Batya Friedman, Takayuki Kanda, Nathan G. Freier, Rachel L. Severson, and Jessica Miller. 2007. “What Is a Human? Toward Psychological Benchmarks in the Field of Human–Robot Interaction.” Interaction Studies 8, no. 3: 363–90.

MacDorman, Karl F., and Hiroshi Ishiguro. 2006. “The Uncanny Advantage of Using Androids in Cognitive and Social Science Research.” Interaction Studies 7, no. 3: 297–337.

Nishio, Shuichi, Hiroshi Ishiguro, and Norihiro Hagita. 2007a. “Can a Teleoperated Android Represent Personal Presence? A Case Study with Children.” Psychologia 50: 330–42.

Nishio, Shuichi, Hiroshi Ishiguro, and Norihiro Hagita. 2007b. “Geminoid: Teleoperated Android of an Existing Person.” In Humanoid Robots: New Developments, edited by Armando Carlos de Pina Filho, 343–52. Vienna, Austria: I-Tech.