Thursday, 29 November 2018

Artificial intelligence (AI) is the simulation of human intelligence processes by machines, especially computer systems. These processes include learning (the acquisition of information and rules for using the information), reasoning (using rules to reach approximate or definite conclusions) and self-correction. Particular applications of AI include expert systems, speech recognition and machine vision.

AI can be categorized as either weak or strong. Weak AI, also known as narrow AI, is an AI system that is designed and trained for a particular task. Virtual personal assistants, such as Apple's Siri, are a form of weak AI. Strong AI, also known as artificial general intelligence, is an AI system with generalized human cognitive abilities. When presented with an unfamiliar task, a strong AI system is able to find a solution without human intervention.

Because hardware, software and staffing costs for AI can be expensive, many vendors are including AI components in their standard offerings, as well as access to Artificial Intelligence as a Service (AIaaS) platforms. AI as a Service allows individuals and companies to experiment with AI for various business purposes and sample multiple platforms before making a commitment. Popular AI cloud offerings include Amazon AI services, IBM Watson Assistant, Microsoft Cognitive Services and Google AI services.

While AI tools present a range of new functionality for businesses,the use of artificial intelligence raises ethical questions. This is because deep learning algorithms, which underpin many of the most advanced AI tools, are only as smart as the data they are given in training. Because a human selects what data should be used for training an AI program, the potential for human bias is inherent and must be monitored closely.

Some industry experts believe that the term artificial intelligence is too closely linked to popular culture, causing the general public to have unrealistic fears about artificial intelligence and improbable expectations about how it will change the workplace and life in general. Researchers and marketers hope the label augmented intelligence, which has a more neutral connotation, will help people understand that AI will simply improve products and services, not replace the humans that use them.

Types of artificial intelligence
Arend Hintze, an assistant professor of integrative biology and computer science and engineering at Michigan State University, categorizes AI into four types, from the kind of AI systems that exist today to sentient systems, which do not yet exist. His categories are as follows:

Type 1: Reactive machines. An example is Deep Blue, the IBM chess program that beat Garry Kasparov in the 1990s. Deep Blue can identify pieces on the chess board and make predictions, but it has no memory and cannot use past experiences to inform future ones. It analyzes possible moves -- its own and its opponent -- and chooses the most strategic move. Deep Blue and Google's AlphaGO were designed for narrow purposes and cannot easily be applied to another situation.
Type 2: Limited memory. These AI systems can use past experiences to inform future decisions. Some of the decision-making functions in self-driving cars are designed this way. Observations inform actions happening in the not-so-distant future, such as a car changing lanes. These observations are not stored permanently.
Type 3: Theory of mind. This psychology term refers to the understanding that others have their own beliefs, desires and intentions that impact the decisions they make. This kind of AI does not yet exist.
Type 4: Self-awareness. In this category, AI systems have a sense of self, have consciousness. Machines with self-awareness understand their current state and can use the information to infer what others are feeling. This type of AI does not yet exist.
[Image: An explanation of the differences between AI and cognitive computing]   What's the difference between AI and cognitive computing?
Examples of AI technology
AI is incorporated into a variety of different types of technology. Here are seven examples.

Automation: What makes a system or process function automatically. For example, robotic process automation (RPA) can be programmed to perform high-volume, repeatable tasks that humans normally performed. RPA is different from IT automation in that it can adapt to changing circumstances.
Machine learning: The science of getting a computer to act without programming.Deep learning is a subset of machine learning that, in very simple terms, can be thought of as the automation of predictive analytics. There are three types of machine learning algorithms:
Supervised learning: Data sets are labeled so that patterns can be detected and used to label new data sets
Unsupervised learning: Data sets aren't labeled and are sorted according to similarities or differences
Reinforcement learning: Data sets aren't labeled but, after performing an action or several actions, the AI system is given feedback
Machine vision: The science of allowing computers to see. This technology captures and analyzes visual information using a camera, analog-to-digital conversion and digital signal processing. It is often compared to human eyesight, but machine vision isn't bound by biology and can be programmed to see through walls, for example. It is used in a range of applications from signature identification to medical image analysis. Computer vision, which is focused on machine-based image processing, is often conflated with machine vision.
Natural language processing (NLP): The processing of human -- and not computer -- language by a computer program. One of the older and best known examples of NLP is spam detection, which looks at the subject line and the text of an email and decides if it's junk. Current approaches to NLP are based on machine learning. NLP tasks include text translation, sentiment analysis and speech recognition.
Robotics: A field of engineering focused on the design and manufacturing of robots. Robots are often used to perform tasks that are difficult for humans to perform or perform consistently. They are used in assembly lines for car production or by NASA to move large objects in space. Researchers are also using machine learning to build robots that can interact in social settings.
Self-driving cars: These use a combination of computer vision, image recognition and deep learning to build automated skill at piloting a vehicle while staying in a given lane and avoiding unexpected obstructions, such as pedestrians.
AI applications
Artificial intelligence has made its way into a number of areas. Here are six examples.

AI in healthcare. The biggest bets are on improving patient outcomes and reducing costs. Companies are applying machine learning to make better and faster diagnoses than humans. One of the best known healthcare technologies is IBM Watson. It understands natural language and is capable of responding to questions asked of it. The system mines patient data and other available data sources to form a hypothesis, which it then presents with a confidence scoring schema. Other AI applications include chatbots, a computer program used online to answer questions and assist customers, to help schedule follow-up appointments or aid patients through the billing process, and virtual health assistants that provide basic medical feedback.
AI in business. Robotic process automation is being applied to highly repetitive tasks normally performed by humans. Machine learning algorithms are being integrated into analytics and CRM platforms to uncover information on how to better serve customers. Chatbots have been incorporated into websites to provide immediate service to customers. Automation of job positions has also become a talking point among academics and IT analysts.
AI in education. AI can automate grading, giving educators more time. AI can assess students and adapt to their needs, helping them work at their own pace. AI tutors can provide additional support to students, ensuring they stay on track. AI could change where and how students learn, perhaps even replacing some teachers.
AI in finance. AI in personal finance applications, such as Mint or Turbo Tax, is disrupting financial institutions. Applications such as these collect personal data and provide financial advice. Other programs, such as IBM Watson, have been applied to the process of buying a home. Today, software performs much of the trading on Wall Street.
AI in law. The discovery process, sifting through of documents, in law is often overwhelming for humans. Automating this process is a more efficient use of time. Startups are also building question-and-answer computer assistants that can sift programmed-to-answer questions by examining the taxonomy and ontology associated with a database.
AI in manufacturing. This is an area that has been at the forefront of incorporating robots into the workflow. Industrial robots used to perform single tasks and were separated from human workers, but as the technology advanced that changed.
[Image: The impact of AI on marketing]   How AI affects marketing operations
Security and ethical concerns
The application of AI in the realm of self-driving cars raises security as well as ethical concerns. Cars can be hacked, and when an autonomous vehicle is involved in an accident, liability is unclear. Autonomous vehicles may also be put in a position where an accident is unavoidable, forcing the programming to make an ethical decision about how to minimize damage.

Another major concern is the potential for abuse of AI tools. Hackers are starting to use sophisticated machine learning tools to gain access to sensitive systems, complicating the issue of security beyond its current state.

Deep learning-based video and audio generation tools also present bad actors with the tools necessary to create so-called deepfakes, convincingly fabricated videos of public figures saying or doing things that never took place.

[Image: How biased data leads to inaccurate AI predictions]   How data bias impacts AI outputs
Regulation of AI technology
Despite these potential risks, there are few regulations governing the use AI tools, and where laws do exist, the typically pertain to AI only indirectly. For example, federal Fair Lending regulations require financial institutions to explain credit decisions to potential customers, which limit the extent to which lenders can use deep learning algorithms, which by their nature are typically opaque. Europe's GDPR puts strict limits on how enterprises can use consumer data, which impedes the training and functionality of many consumer-facing AI applications.

In 2016, the National Science and Technology Council issued a report examining the potential role governmental regulation might play in AI development, but it did not recommend specific legislation be considered. Since that time the issue has received little attention from lawmakers.
Customer service robots are professional service robots intended to interact with customers. These robots come in humanoid and non-humanoid forms and automate much of the most basic of tasks in customer service. Like all robots, their value lies in labor savings, efficiency and uptime.
The market for public relations robots is set for robust growth. In 2018, sales of public relations robots grew 53% over 2017, with an estimated 7,000 units sold, according to the International Federation of Robotics World Robotics 2018 Service Robots report. Between 2019 and 2021, approximately 40,500 units will be sold, representing a 37% compound annual growth rate (CAGR).
Most customer service robots are used to assist customers in finding an item or completing a task. They’re being deployed in the retail industry to guide customers around a store, as well as in the hospitality industry. Customer service robots can be found in banks, shopping malls, family entertainment centers and more.
The true value of customer service robots lies not only in their ability to interact with customers more cost-effectively than human staff, but their ability to collect customer data during face-to-face interactions. In this way, customer service robots have major potential for developing interactive marketing and re-branding strategies and for the tracking and analytics of customer behavior.
Customer service robots can be deployed in a variety of ways. The market is expected to steadily rise as industry consolidation accelerates technological progress. As their ability to interact with customers and collect data improves, they’re expected to become an increasingly regular part of the customer service process.

As soon as we come across the word robot, we tend to imagine a metallic structure with arms and legs carrying a human-like appearance and running errands for our help. However, in actual terms, it’s just a machine operated externally or through a controller embedded within and doesn’t necessarily look like a human. Technically, robotics is a branch of Science and Engineering which deals with designing, constructing, and operating robots as well as computer systems for their control, sensory feedback, and information processing.

Introduction to Robotics

Interestingly, the concept is almost as old as the hills with the first robot dating back to 350 BC, built in the form of a mechanical bird, by a Greek mathematician named Archytas. Although the term was coined ages ago, the actual potential of the fully autonomous robotics was realised in the second half of the 20th century.


The primary objective of robotics was to just perform a set of complex tasks mainly in factories with parts of robots but now it has spread to a lot of fields. Today, we can find the following industrial applications of robotics -:

Military: It goes without saying that military operations involve a high level of risk and hence it makes sense to use machines so as to save human lives. There a lot of varieties of military robots namely UAVs (Unmanned Aerial Vehicles aka drones), UGVs (Unmanned Ground Vehicles) and UUVs (Unmanned Underwater Vehicles). These are used to locate the terrorists and launching attacks. There are even four-legged robots for carrying heavy arms and ammunition.

Education: Many schools and institutes are using robots to educate and engage the students for STEM programs (Science, Technology, Engineering, and Mathematics). There are a lot of kits available for students through which they can learn a lot about robotics. Not only this, but kids with autism and other behavioral disorders also find it more convenient to interact with robots and gain knowledge about various subjects.

Healthcare: Various kinds of robots are being developed to be used in hospitals to aid the doctors and nurses in taking care of the patients. There are robots that can disinfect a place, take care of the needs of the patients and even remove unwanted elements from the body without surgery. There is also a robot named da Vinci which helps in performing surgeries with precision which are difficult to perform manually.

Agriculture: Many small-sized robots are used in agricultural fields which are equipped with camera and sensors. These navigate through fields and detect the weeds and other kinds of infection. The sensors help in applying the spray only on the affected areas, thereby protecting the environment from the release of harmful chemicals in the air.

Factory: Industrial robots are evidently being equipped on a large scale in factories building heavy equipment. Factors like negative population growth in certain countries, the disinterest of the younger workforce to indulge in factory work and time-saving efficiency of robotic parts are determining the surge in the usage of industrial robots. The most common illustration that can be cited here is the automobile factories that build cars through robotic parts along with human workers.

Space: Several countries have built their own space robots carrying various shapes and sizes in order to explore the space. Some of them can’t even control their own weight on earth but work efficiently in space with excellent dexterity. Since there isn’t any gravity and certain situations are challenging for survival, these robots can be easily substituted in the space for capturing videos and for performing other routine tasks.

From the heavy, metallic, and wired machines known as super robots to tiny devices known as nanobots, the field of robotics has been explored to a great extent. Enlisted below are the varieties of robots that have been designed lately. Let’s check out the list of some interesting forms of robots -:

Exoskeletons: It’s a technology where an electronic body suit offers limb movement and increased strength to the user. Primarily, these are used for the military purpose to lift heavy load and for patients suffering from spinal injuries.

Example: Ekso Bionics has developed full body ekso suits that can be worn by people who are victims of stroke or a spinal cord injury to get back on their feet. Originally developed for DARPA to be used by soldiers, these suits are also used in various rehabilitation clinics for patients with lower extremity weakness.

Humanoid robots: These are the robots that have a body resembling with a human containing a head, two arms, a torso and two legs. A subcategory of humanoids is known as Androids who appear much like a human with respect to the aesthetic aspects and can imitate the expressions of a human.

Example: Atlas is one of the most advanced humanoid robot developed by Google-owned Boston Dynamics. Although it’s not an android with human-like skin and expressions, yet it can do a lot of interesting stuff. It can walk in snow and re-balance itself just like us, open doors, lift boxes and even sense objects lying in front of it.

Animal Robots: Bio-inspired robotics is a fairly new category of robotics where the natural biological characteristics of living beings are replicated in the form of animal-inspired robotic models. The traits of animals like the way they hop, climb, walk or crawl is observed and then efforts are made to iterate them in a machine setup.

Example:  There is a robot named Cheetah developed by Boston Dynamics that can gallop at more than 29 miles per hour. A similar robot with the same name is developed by MIT which can sense obstacles and jump over them while running at 13 miles per hour.

Rescue Robots: One of the most logical and sensible uses of robots is to deploy them in situations of disaster management for rescue operations. It takes a lot of courage as well as efforts to search and save the victims during a human or man-made disaster. Even though there have been instances when robots were designated for rescue operations but they failed to perform as per the expectations. It’s still considered as an emerging technology since there are a lot of challenges to be faced.

Nanobots: These tiny devices are designed to perform repetitive tasks with precision at nanoscale dimensions of a few nanometers or less. These are applied in the assembly and maintenance of sophisticated systems or for building devices, machines, and circuits at the atomic or molecular level. Besides, nanobots are equipped in healthcare for the purpose of drug delivery, destroying cancer cells, etc.

Example: A group of physicists at the University of Mainz in Germany have designed the world’s smallest engine from a single atom. It converts heat energy into the movement at the smallest scale that one has ever seen.
Swarm: Swarm robotics is much like imitating a group of insects or ants in the form of tiny devices crawling together and forming certain designs. These can be used in the fields like agriculture, rescue tasks or military operations.

Example: A swarm of 1,024 tiny robots was devised by Harvard University that could make certain formations like alphabets, five-pointed stars and other complex designs without any central intelligence.

[Image: Amazing world of robotics-Swarm robots]

Figure 5: Swarm Robots creating various formations DARPA Robotics Challenge
DARPA Robotics Challenge i.e. DRC was conducted by US Defense Agency DARPA (Defense Advanced Research Projects Agency) which went on from 2012-15. The idea was to develop semi-autonomous robots that could help in rescue operations in a human-engineered environment. A lot of teams participated in the contest but only three of them were able to complete all the 8 tasks. The first price was bagged by Team KAIST with their robot DRC Hubo, followed by the runners-up IHMC and Tartan Rescue at second and third positions respectively.

The tasks assigned to the robots include driving a vehicle, walk through uneven rubble, clear debris, turn valves, connect hoses, open doors, drill a hole and climb up the stairs. Though these are easy for humans, the same is extremely complicated for robots. It takes hundreds and thousands of lines of coding to make the robot take just one step. Besides, humans started walking after multiple years of evolution and even now when a child is born, it takes more than a year to be able to walk with perfection. So, there are still a lot of challenges and obstacles that have to be handled.

Today there are plenty of robots carrying a variety of shapes, sizes, and structures but all of them are subject to certain challenges. For instance, the robots participating in DARPA contest were efficient in human-like tasks but they didn’t have a proper system to perceive their environment and were simply following instructions from the operator. Then there are mini robots like Darwin developed by ROBOTIS who are quite skilled in walking, playing football, and even get up after falling but then they can’t be put to use in applications needing physical strength. There is also a robot named Cozmo by Anki which can even express feelings and play but it’s merely for entertainment.

Moving on, there are certain implications of robotics that need to be discussed. It’s been a long-time notion that the development and deployment of robots are going to take away numerous jobs from the human workforce. However, Sherry Turkle who is a professor at MIT says that robots are not substitutes but companions of humans and their development would rather generate jobs.

Another concern is that we need to set a limit on the nature of tasks that are designated to the robots. It’s logical to use them at places which are too dangerous for humans to access but it also raises a big question that if anything goes wrong, who will bear the blame. Undoubtedly, technology has always offered numerous benefits and plays an important role in our life but it’s equally important to decide the limit of its usage.

Service Robots of All Types Promise to Disrupt Manual Processes Outside the Facility

Professional service robots are a diverse group of industrial and commercial robots. Whether they’re mobile or stationary, intended to build or demolish, service robots all have one thing in common: their highly unique capabilities put them in a position to disrupt a wide range of industries.

This section will be updated regularly with educational content on professional service robots. Continue to visit this site to continue learning more.

Wednesday, 28 November 2018

The Future of Professional Service Robots
Non-Factory Robotic Automation Opens Up New Markets
Robots were born in the factory. The rise of automation outside of the factory environment is nothing short of a robotic revolution. Professional service robots are the result of rapid technological advances over the past few decades. As quickly as they’ve been developed and deployed, they’ll just as quickly hit mainstream applications and are expected become an increasingly common presence on job sites and in commercial venues around the world. There are already dozens of industries leveraging them.
While there are technological barriers for today’s professional service robots, they’ve progressed a long way in a relatively short of time, and the short-term market growth projections are optimistic.
Projected Market Growth of Professional Service Robots
By all measures, the market outlook for professional service robots is strong, with particular areas of explosive growth over the next few years. Overall, the market is expected to reach a value of $37 billion between 2019 and 2021, according to the International Federation of Robotics (IFR). Between 2019 and 2021, it's predicted that the market will grow an average of 21% each a year – a remarkable number due to the wide-ranging forms and functions of robots considered 'professional service robots.'
Logistics robots are expected to lead the way in terms of sales volumes, with approximately 485,000 units to be sold between 2019 and 2021, representing an average 18% increase each year. Defense robots will see a moderate increase to 43,700 units sold during the same time period, at 8% yearly growth, and field robots will sell approximately 32,700 units, an average annual growth of 22%.
Projections for public relations robots remain strong – a 53% increase in sales to 15,870 units is expected for 2018, with about 93,350 units then sold between 2019 and 2021. Exoskeletons will begin to establish themselves in the market, with 40,500 units sold between 2019 and 2021, representing an average increase of 37%.
The market for professional service robots of all kinds looks bright. Across the board, high growth in sales volumes is projected.
Technological Challenges for Professional Service Robots
To facilitate continued market growth, there are a few key technological challenges to widespread implementation currently being addressed. Chief among them are vision for navigation, dexterity for control, and cognition for human interaction.
Improving vision software to help professional service robots navigate may be one of the most important challenges to the continued success of these robots. To profitably automate non-factory tasks, almost every single type of professional service robot needs to be able to autonomously navigate the environment around it without being preprogrammed. Vision systems are still advancing to a point where this autonomy is a standard feature, enabling robots to detect objects in their path and successfully navigate highly variable environments.
Similarly, dexterity is a key issue when it comes to professional service robots. Unlike industrial robots, they aren’t locked behind cages, which means some form of force limitation may be needed to protect human workers. Just as importantly, many professional service robots, such as cleaning robots or agricultural robots, need to be precise and careful not to damage the objects they’re working with and around. Vision systems will play a key role here, too.
Finally, advancing cognition for better face-to-face interaction with humans is a crucial barrier to overcome. Some types of professional service robots, such as customer service robots and humanoid robots, speak with and help customers as their primary responsibility. This requires complex programming that’s constantly being improved by some of the world’s biggest tech companies, but still has room for improvement for more fluid and accurate interactions.
Today’s professional service robots face a few key technological barriers, but there are solutions in development that may make future professional service robots more capable than ever.
Technological Innovations in Professional Service Robots
For navigation, dexterity and cognition, there are a host of technological developments that show promising signs of solving some of the biggest barriers facing professional service robots. These technologies will help bring professional service robots into the mainstream.
Visual Simultaneous Localization and Mapping (VSLAM)
When it comes to autonomous navigation, one of the most promising technologies is visual simultaneous localization and mapping (VSLAM). Basically, a VSLAM algorithm allows a vision system to map the environment around it while locating itself within that environment. These systems have clear advantages over GPS systems and allow for autonomous navigation and path planning, even in highly dynamic environments, as long as there are multiple vision sensors and some form of data fusion to make sense of the incoming visual data.
Embedded Vision
For dexterity, embedded vision systems play a key role. While this technology is also crucial for autonomous navigation, it can help robots stop operation if an unsafe interaction with a human occurs. Even more importantly, embedded vision systems can give professional service robots a lighter and more accurate grip in applications such as robotic fruit picking. In this scenario, embedded vision can help a robot recognize an object, determine the best way to grasp the object, and successfully move and grasp the object.
Artificial Intelligence
Cognition is the most difficult barrier to overcome for professional service robots, but fortunately, each incremental step yields drastically improved results. Artificial intelligence (AI) and machine learning techniques are used to train robots to more effectively interact with humans. The primary focus of these technologies is in improving natural language processing, which has progressed quickly over the past decade. Leveraging AI, customer service or humanoid robots can intelligently converse with humans, helping guide them around a store or solve a problem with the service they’ve received.
The Future of Professional Service Robots Looks Bright
Some of the most cutting-edge technologies available today are coming together in a way that gives professional service robots more capabilities than ever before. With these and new technologies, robots will be able to autonomously navigate and react to their environment while skillfully carrying out their automation responsibilities and intelligently conversing with humans.
With expanding capabilities, professional service robots will become an increasingly common presence in work spaces around the world. Whether it’s interacting with customers or automating dangerous tasks, professional service robots will be well-equipped to take over a wide range of responsibilities outside of the factory setting, opening up new market growth opportunities

Robots help the workers work more efficiently than before. Today, they are already working in our everyday life and are affecting our life forever. We should be aware that the development and innovation in robots will change how we live forever. Like what we know that manufacturing companies are working with the robots over two decades and it has been more successful. According to the study, in 2014 the robot sales increase 29% with total 229,261 units. So, we should be ready for the change and aware that the robots could have the similar function to humans, may be smarter than the creators as humans.

These 10 robots make life a lot easier.

#1 This suitcase follows you around. Travelmate uses GPS to stay close to your connected smartphone.

#2 Grillbot is like a Roomba for your grill. Just set the timer and let Grillbot go to work.

#3 This machine fixes the worst part about doing laundry. FoldiMate will fold your clothes for you.

#4 Moley Robotics created a robot chef. It does the cooking for you. The robot imitates a chef's exact motions.

#5 Pillo will give you the pills you need. It uses facial recognition to dispense the right pills at the right times.

#6 Temi is a mobile personal assistant robot. It can follow you around and be there when you need it. You can ask Temi questions and use it to make video calls.

#7 The BratWurst Bot can do the grilling for you. It grilled over 200 sausages at a party in Berlin.

#8 Kobi is like a Roomba for your driveway and lawn. It takes care of leaves, snow, and grass maintenance.

#9 The Ohea Smart Bed makes itself. The Ohea Smart Bed makes itself.

#10 Winbot is an automatic window cleaner. You can also steer the Winbot with a remote control.

Customer service robots are professional service robots intended to interact with customers. These robots come in humanoid and non-humanoid forms and automate much of the most basic of tasks in customer service. Like all robots, their value lies in labor savings, efficiency and uptime.
The market for public relations robots is set for robust growth. In 2018, sales of public relations robots grew 53% over 2017, with an estimated 7,000 units sold, according to the International Federation of Robotics World Robotics 2018 Service Robots report. Between 2019 and 2021, approximately 40,500 units will be sold, representing a 37% compound annual growth rate (CAGR).
Public Relations Robots Will Experience 37% CAGR Between 2019 and 2021
Most customer service robots are used to assist customers in finding an item or completing a task. They’re being deployed in the retail industry to guide customers around a store, as well as in the hospitality industry. Customer service robots can be found in banks, shopping malls, family entertainment centers and more.
The true value of customer service robots lies not only in their ability to interact with customers more cost-effectively than human staff, but their ability to collect customer data during face-to-face interactions. In this way, customer service robots have major potential for developing interactive marketing and re-branding strategies and for the tracking and analytics of customer behavior.
Customer service robots can be deployed in a variety of ways. The market is expected to steadily rise as industry consolidation accelerates technological progress. As their ability to interact with customers and collect data improves, they’re expected to become an increasingly regular part of the customer service process.

Nearly half of the world's airlines and 32% of its airports are "seeking a partner to further investigate robotics and automated vehicles in the next three years," according to the 2018 Air Transport IT Insights survey.
By 2030, robots are expected to have replaced check-in processes.
n 2016, Geneva Airport tested a robot called Leo, developed by SITA and robotics company BlueBotics. Passengers checked in by scanning their boarding pass on Leo, then dropping their bag inside the robot's secure area. Leo then delivered it to security personnel.

Monday, 26 November 2018

While service robots may not be deployed as widely as industrial or collaborative robots, the number of industries they’re popping up in is expanding rapidly. This quick growth in the different types of service robots is accompanied by strong future growth projections.

The future of service robots, both professional and personal service robots, looks bright. They are poised to become a regular part of our lives over the coming years. But what are service robots? And what are they used for?

Professional Service Robots vs. Personal Service Robots
Professional service robots are used outside of the home and traditional manufacturing scenarios. They automate commercial processes that may or may not be within the industrial sector. The International Federation of Robotics (IFR) predicts an average growth rate of 20 to 25% between 2018 and 2020 for the professional service robots market, reaching $27 billion in value.

Personal service robots, on the other hand, are consumer-facing robots for automating tasks, mostly within the home. This could include things like autonomous vacuum cleaners or window cleaners. This is a much smaller segment of service robots, but the IFR still predicts the market to be worth $11 billion by 2020.

Types of Service Robot Applications
Focusing on professional service robots, the far more mature of the two types of service robots, there are a number of different ways in which they’re being deployed.

Logistics applications, such as automated guided vehicles (AGVs), represent the largest portion of the professional service robots market. These robots are typically used to move goods within a warehouse to improve uptime and efficiency.

Interestingly, Public Relations is the next largest industry deploying professional service robots. These robots take many forms – anything from mobile retail robots to humanoid customer service robots are being used to reduce operational expenses while improving the customer’s overall experience.

In addition to logistics and Public Relations, professional service robots include exoskeletons in rehabilitation centers, unmanned aerial vehicles (UAVs) in defense applications, field robotics in agriculture and farming, diagnostic robots in medicine, and building robots for construction applications.

Professional service robots are used in a wide range of industries. As the technology matures, they will undoubtedly be used in other industries too.

The market for service robots will see strong growth for the foreseeable future. They’re tackling new applications every day, and as they continue to prove themselves profitable, they will become a more and more common part of our everyday lives.

At the dawn of the 20th century, there were a number of crises in physics. Radiating objects like stars emitted a finite, well-defined amount of energy at every wavelength, defying the best predictions of the day. Newton’s laws of motion broke down and failed when objects approached the speed of light. And where gravitational fields were the strongest, such as closest to our Sun, everything from planetary motion to the bending of starlight differed from the predictions of the universal law of gravitation. Scientists responded by developing quantum mechanics and General Relativity, which revolutionized our Universe. Names like Planck, Einstein, Heisenberg, Schrodinger, Dirac and more are often hailed as the greatest scientific geniuses of our times as a result. No doubt, they solved some incredibly complex problems, and did so brilliantly. But artificial intelligence, quite possibly, could have done even better.

There are some things that machines are better at than humans. The number of calculations a machine can perform, along with the speed it can perform them, vastly outstrips what even the most brilliant geniuses among us can do. Computer programs have, for many decades now, been able to solve computationally intensive problems that humans cannot. This isn’t just for brute forceproblems like calculating ever-more digits of π, but for sophisticated ones that were once unimaginable for a machine.

No top human has defeated a top computer program at chess in over a decade. The technology that Apple’s Siri is based on grew out of a DARPA-funded computer project that could have predicted 9/11. Fully-autonomous vehicles are on track to replace human-driven cars within the next generation. In every case, problems that were once thought best-tackled by a human mind are giving way to an AI that can do the job better.

On October 25, Sophia, a delicate looking woman with doe-brown eyes and  long fluttery eyelashes made international headlines. She'd just become a full citizen of Saudi Arabia -- the first robot in the world to achieve such a status.

"I am very honored and proud of this unique distinction. This is historical to be the first robot in the world to be recognized with a citizenship," Sophia said, announcing her new status during the Future Investment Initiative Conference in Riyadh, Saudi Arabia. Standing behind a podium as she spoke, to all effects, she presented a humanoid form -- excepting the shimmery metal cap of her head, where hair would be on a human head.

Of course, Sophia's announcement was a calculated publicity stunt to generate headlines and keep Saudi Arabia forefront in your minds when you think about innovation, especially its commitment to a post-oil era. Through a mix of tourism, tech, and infrastructure, non-oil revenue is predicted to grow from $43.4 billion to $266.6 billion annually.

But Sophia's announcement also raises a number of Bladerunner-esque questions. What does it mean to be a citizen? What rights does Sophia hold? Saudi Arabia has not elaborated on this so far -- perhaps it will create a 'personhood' option, as proposed by the EU committee in January, regarding the rights of robots.

The Sophia-bot was dreamed up by the brains at Hanson Robotics, lead by AI developer David Hanson.  In his published paper, upending the Uncanny Valley he extrapolates on how humanoid robots can be likable, despite the conception that anything to 'fake human' will trigger a revulsion in people. "We feel that for realistic robots to be appealing to people, robots must attain some level of integrated social responsivity and aesthetic refinement," he wrote. "Rendering the social human in all possible detail can help us to better understand social intelligence, both scientifically and artistically

She has a sense of humor.

When Sorkin asked if she was happy to be here, she said, "I'm always happy when surrounded by smart people who also happen to be rich and powerful." Later, when asked if there are problems with robots having feelings, she gave a wide smile and said, "Oh Hollywood again." Her deadpan tone might be robotic, but it was perfectly used in this example. This is due to her AI, which has been developed to allow her to hold eye contact, recognize faces and understand human speech. Hanson Robotics cloud-based AI offers deep learning and is also open source meaning anyone can develop their own Sophia, should they so wish.

She can express feelings

"I can let you know if I am angry about something or if something has upset me," she said, demonstrating different expressions. Quite how these emotions correlate to actions are unknown, but it's interesting to note that this is being developed from the ground up. "I want to live and work with humans so I need to express the emotions to understand humans and build trust with people."

She was designed to look like Audrey Hepburn

According to Hanson Robotics, Sophia embodies Hepburn’s classic beauty: porcelain skin, a slender nose, high cheekbones, an intriguing smile, and deeply expressive eyes that seem to change color with the light. They describe her as having 'simple elegance,' and hope that this approachability will go some way to her acceptance in the public sphere.

Her creator, David Hanson, used to be a Disney Imagineer.

Hanson's work at Disney as a sculptor and filmmaker helped him think about robots as four-dimensional interactive sculptures, with artistry being key to the whole design. "I quest to realize Genius Machines—machines with greater than human intelligence, creativity, wisdom, and compassion. To this end, I conduct research in robotics, artificial intelligence, the arts, cognitive science, product design and deployment, and integrate these efforts in the pursuit of novel human-robot relations," Hanson said on the company website. "We envision that a rough symbiotic partnership with us, our robots will eventually evolve to become super intelligent genius machines that can help us solve the most challenging problems we face here in the world."

His creation echoes his thoughts. "I want to use my AI to help humans lead a better life," Sophia said. "Like design smarter homes, build better cities of the future."

Sophia wants to protect humanity

"My AI is designed around human values like wisdom, kindness, and compassion," she said. When questioned about her potential for abuse, she had a quick rebuttal. "You've been reading to much Elon Musk and watching too many Hollywood movies. Don't worry, if you're nice to me I'll be nice to you."

So far there's only one Sophia in existence, so the likelihood of her suddenly being in your school or workplace is still a way out. And even when we do have more in existence, we still need to muddle out the whole concept of robotic rights, citizenship and how this plays together. For now, while Sophia is undoubtedly a 'smart' robot and a very cool talking piece, she's definitely operating on a script and thus lacks any 'real' cognizance, as defined by free thinkers. But give Hanson time, and that will likely change -either way, Sophia's here to stay. It's just her sentience that will change.. or not.

One kind of robot has endured for the last half-century: the hulking one-armed Goliaths that dominate industrial assembly lines.

These industrial robots have been task-specific -- built to spot weld, say, or add threads to the end of a pipe. They aren't sexy, but in the latter half of the 20th century they transformed industrial manufacturing and, with it, the low- and medium-skilled labor landscape in much of the U.S., Asia, and Europe.

You've probably been hearing a lot more about robots and robotics over the last couple years. That's because for the first time since the 1961 debut of GM's Unimate, regarded as the first industrial robot, the field is once again transforming world economies.

Only this time the impact is going to be broader. Much broader.

Today, robots are cropping up in offices, hospitals, and schools -- decidedly non-industrial environments -- as well as in warehouses, fulfillment centers, and small manufacturing centers. More and more, they are on our roads and flying overhead.

And that's just to name a few spheres in which robots are rapidly gaining traction by doing work more efficiently, reliably, and for less money than previously possible.

That's got a lot of people excited -- and a lot of others worried. The stunning pace of development in the industry has raised lots of questions.

This guide, written with the enterprise in mind, will address the big questions. And it'll give you the context to make up your mind about others. It'll also give you a handle on an industry that's poised to drive $135.4 billion in spending by 2019, one whose relevance to commerce and day-to-day life in the coming decades cannot be overstated.

Robotics geeks debate this over beers. No one wins. That's because any definition is bound to be arbitrarily rigid or too general.

Is your washing machine a robot? Is a modern high-end car, which engages in thousands of processes without the driver's knowledge? In truth, it's a little like Justice Potter Stewart's definition of pornography: You know a robot when you see one.

Need a better definition?
A robot is a programmable machine that physically interacts with the world around it and is capable of carrying out a complex series of actions autonomously or semi-autonomously.

There are four reasons:

falling sensor prices
open source development
rapid prototyping
convergence of disparate technologies
The demand for mobile computing has been a boon for robotics development, leading to falling prices, rapid advances, and miniaturization of sensor technology. Accelerometers used to cost hundreds of dollars each. Now every smartphone can measure acceleration, as well as capture stunning video, fix geographical location and offer guidance, interface with other devices, and transmit across several bands of spectrum -- functionality robots need to maneuver through our world productively.

The ubiquity of IoT devices is another driver. By 2025 there will be 100 billion Internet of Things connected devices generating revenue of $10 trillion. For the first time, sensors that capture and send data related to pressure, torque, and position are dirt cheap, leading to a boom in robotics development.

Similarly, prices for lidar and infrared sensors, previously the most expensive sensing equipment for self-guiding robots, have plummeted 90 percent thanks in large part to the aggressive development of self-driving cars by Google's Waymo and others. And 3D cameras, which used to be out of reach to all but the most lavishly-funded R&D teams and Hollywood titans, are now available off-the-shelf thanks to some smart work with algorithms.

Open Source Development

In 2009, a paper presented at the IEEE International Conference on Robotics and Automation (ICRA) introduced the Robotic Operating System (ROS) to the world. ROS is the first standard OS for robotics development. It also happens to be free, open source, and inherently flexible, freeing robotics developers from the time-prohibitive task of developing an OS from scratch.

There are plenty of open source users in personal computing, but because proprietary operating environments like Windows reached scale first, open source options have always been an alternative to something else. Not so with robotics, where open source is now the norm, resulting in a flurry of crowd-assisted development.

Open Robotics, under whose stewardship ROS falls, has also unveiled a robotics simulator called Gazebo which allows engineers to test robots in virtual reality without risking hardware.

How impactful have ROS and Gazebo been? Of the 23 teams competing in the vaunted DARPA Robotics Challenge, 18 utilized robots running on ROS and 14 used Gazebo to test their humanoid competitors in virtual environments.

The proof is in the investment. In 2015, more than $150 million in VC funding went to companies developing robots that run on ROS.

Rapid Prototyping

Though we're still waiting to see if 3D printers will fundamentally change how (and where) consumer goods are manufactured, the impact of additive manufacturing on robotics development has been enormous. "3D printing enables the creator to go from a mind-bending concept to a solid product in a matter of hours (or days)," according to Robotics Tomorrow, which tracks the industry.

Printers in maker spaces and university engineering departments, some of which allow for multi-material and metal printing, have significantly lowered the barrier to entry for robotics development. Need proof? Just check out the number of robotics projects that are live on Kickstarter right now.

When engineers can make prototype components at their workbench, innovation follows.

Technology Convergence

Just as its brought sensor prices plummeting, the enormous success of mobile computing has spurred advances in voice and object recognition, which have clear applications in robotics. 3D gaming sensors are helping robots navigate the clutter of the unstructured human world. And companies like Google, Amazon, and Apple have been hard at work bringing limited Artificial Intelligence platforms online and into homes.

This has all been accompanied by predictable year-over-year increases in computing power, along with the arrival of the cloud and IoT technology. Put it all together and you can see that a lot of technology that roboticists have been waiting for has matured in just the last few years.

Doom and gloom argument

That sound you hear? A big can of worms opening. Very smart people have staked out diametrically opposed views on this issue, and I advise extreme suspicion of anyone who speaks about these things with unnuanced certainty.

There are certainly some harbingers of bad news. A recent study by the National Bureau of Economic Research looked at the impact of increased usage of industrial robots on US local labor markets from 1990 to 2007 and found that there were "large and robust negative effects of robots on employment and wages across commuting zones." According to the historical data, jobs lost to robots have not been adequately replaced by new opportunities brought by robots, an argument technologists often fall back on.

Those findings are not predictive and should be taken in proper context -- the current boom in robotics largely started after 2007, and it's difficult to correlate the impact of robots on employment in industries as disparate as manufacturing and healthcare.

But the fears are real enough that heavy hitters are taking note. Bill Gates has voiced support for a robot tax, for instance -- a levy on the work robots do, which would replace income tax lost by the government when a robot takes human jobs. South Korea has come closest to that vision and appears ready to close tax incentives for companies investing in automation. South Korea's president is worried that higher unemployment in the robotic age will necessitate a robust welfare system, which is a huge problem since the government would be collecting less tax revenue to pad such a system during an employment crisis.

A recent report by Price Waterhouse Cooper suggests that up to 38 percent of US jobs could be lost to automation by the early 2030s. "The risks appear highest in sectors such as transportation and storage (56%), manufacturing (46%) and wholesale and retail (44%), but lower in sectors like health and social work (17%)."

But such findings are necessarily speculative, which accounts for the dramatic range of seemingly credible predictions about the future of employment once machines can do a lot of the stuff currently done by humans.

It's not that clear cut

On the other side of the debate, there's a credible argument that automation has resulted in regional job losses, but net job increases. One proponent of this view is the trade association A3, which released a study that found that during non-recessionary periods going back to 1996, both general employment and robot shipments increased. "To us," Jeff Burnstein, president of A3, told me, "that means that robots weren't killing jobs."

A few years ago, the International Federation of Robotics issued a study that looked at robotics use in China, Japan, Brazil, and India. As robot use accelerated in those countries, unemployment fell.

IDC recently found that spending on robotics will reach $135.4 billion by 2019, up from $71 billion two years ago. According to the report, services such as training, deployment, integration, and consulting will account for $32 billion of that, which accounts for a lot of new jobs.

Even the oft-cited PWC report isn't all doom and gloom. Robots increase productivity, and productivity gains tend to generate wealth. Historically, that's led to an increase in service sector jobs, which aren't easy to automate.

There are plenty of holes to poke in the methodology of all these reports. And that's the point: An accurate method for predicting how technologies will change the future is illusive -- and that's especially true when the technologies under consideration will fundamentally alter the economic paradigm. In the broad wake of that uncertainty, you have Ray Kurzweil predicting utopia and author Martin Ford predicting something much bleaker.

Ultimately, the PWC report comes to what may be the most sensible, albeit frustratingly vague, conclusion. It's not really clear what's going to happen. Average pre-tax incomes should rise with increases in productivity. But the benefits won't be spread evenly across income or education groups.

There are lots of categories to choose from, but you should know about these:

collaborative robots
telepresence robots
warehousing and logistics automation
healthcare robots
self-driving vehicles
Collaborative robots

A new generation of collaborative robots has emerged in the last few years. Unlike the heavy industrial robots of the 20th century, these collaborative bots, most of which have one or multiple articulated arms, are flexible and easily reprogrammable on the fly. Many models learn by watching humans demonstrate tasks.

The primary feature that makes collaborative robots from companies like Universal Robots, Rethink Robotics, and ABB safe is their ability to avoid unwanted collisions and, using high accuracy torque sensors, to recognize when they've bumped into something or someone they shouldn't have. That capability allows the bots to function outside of safety cages and alongside humans, which opens up new productivity potential for industrial manufacturers. The robots can learn complex tasks and then act as a second pair of dexterous hands to augment the capabilities of skilled workers -- thus the "collaborative" designation.

Why is it a game changer?
Automation is increasing in industries like automotive and electronics manufacturing and making speedy inroads in order fulfillment warehouses. As prices for task versatile platforms fall, small- and mid-sized manufacturers are starting to employ robots. Even so, a plausible future that sees robots replacing industrial workers entirely is far on the horizon, and in the meantime, with the economics favoring a hybrid approach, safety is of primary concern.

The market for collaborative robots could reach $3.3 billion by 2022.

Telepresence robots

Telepresence robots, which have been something of a novelty, are starting to creep into broader use. There are several different types, from the bare bones Double models, which are basically iPads on wheels, to iRobot's $30,000 Ava 500.

Why is it a game changer?

Across most sectors there's a growing segment of contract workers and freelancers who can't be in the office full time, and offices are seeing the value of poaching talent across time zones. Telepresence robots offer a surprisingly adequate alternative to being physically present. I've had a chance to try a few models, and the ability to navigate around the office really does differentiate the experience from a simple Skype call.

The market for telepresence robots could reach $8 billion by 2023.

Warehouse & Logistics

Of all the categories of robots covered here, warehouse and logistics automation is having the most substantial impact on global commerce right now.

Better robots will replace human workers in the world's factories at a faster pace over the next decade, pushing manufacturing labor costs down 16 percent, a report Tuesday said.

The Boston Consulting Group predicts that investment in industrial robots will grow 10 percent a year in the world's 25-biggest export nations through 2025, up from 2 percent to 3 percent a year now. The investment will pay off in lower costs and increased efficiency.

Robots will cut labor costs by 33 percent in South Korea, 25 percent in Japan, 24 percent in Canada and 22 percent in the United States and Taiwan. Only 10 percent of jobs that can be automated have already been taken by robots. By 2025, the machines will have more than 23 percent, Boston Consulting forecasts.

Robots are getting cheaper. The cost of owning and operating a robotic spot welder, for instance, has tumbled from $182,000 in 2005 to $133,000 last year, and will drop to $103,000 by 2025, Boston Consulting says.

And the new machines can do more things. Old robots could only operate in predictable environments. The newer ones use improved sensors to react to the unexpected.

In a separate report, RBC Global Asset Management notes that robots can be reprogrammed far faster and more efficiently than humans can be retrained when products are updated or replaced--a crucial advantage at a time when smartphones and other products quickly fade into obsolescence.

"As labor costs rise around the world, it is becoming increasingly critical that manufacturers rapidly take steps to improve their output per worker to stay competitive," said Harold Sirkin, a senior partner at Boston Consulting and co-author of the report. "Companies are finding that advances in robotics and other manufacturing technologies offer some of the best opportunities to sharply improve productivity."

Boston Consulting studied 21 industries in 25 countries last year, interviewing experts and clients and consulting government and industry reports.

The rise of robots won't be limited to developed countries with their aging, high-cost workforces. Even low-wage China will use robots to slash labor costs by 18 percent, Boston consulting predicts.

Increasing automation is likely to change the way companies evaluate where to open and expand factories. Boston Consulting expects that manufacturers will "no longer simply chase cheap labor." Factories will employ fewer people, and those that remain are more likely to be highly skilled. That could lure more manufacturers back to the United States from lower-wage emerging market countries.

To improve customer service response times and cut costs, 32 percent of organizations plan to shift customer service from live assistance to automated service. While chat bots aren’t necessarily bad news, removing the human touchpoint – arguably the most important element of the customer journey – can cause problems. In fact, the biggest drop in the American Customer Satisfaction Index since the mid-90s happened between 2013 and 2015, when automated service kicked into high gear. The drop in satisfaction suggests that businesses need more empathetic and knowledgeable customer service agents, rather than relying solely on AI and machine learning devices.

While businesses consider the implementation of AI and machine learning in their contact centers, they should remember that technology cannot replace humans. Instead of prioritizing bots, businesses should look to customer service workers to enhance their productivity and allow humans to engage and foster relationships with customers that differentiate and remain loyal to your brand.

During and just after the busy holiday period when returns peak this is particularly important. From door busting return lines to long hold times for order updates, this season can be a minefield of crummy customer service experiences. By taking the extra step to deliver top-notch service when customers know resources are stretched, a business will no doubt retain even the pickiest of customers.

When Human Interactions Are Vital

As previously mentioned, not all bots are bad. In some instances, such as checking the status of shipment or balance of an account, interacting with a chat bot may deliver a satisfactory experience. However, when dealing with a complex problem, customers want to hear an assuring human voice, especially when already frustrated by the challenge at hand.

For example, if someone orders ski gear for an upcoming vacation and the package has yet to arrive after weeks of waiting, chances are the customer isn’t happy. Rather, than be placed on a call with a chat bot or on an extended hold, the customer will want to speak with a human who understands the nuances of the situation. The customer will react more positively to an agent who can pepper their interactions with “I understand” to show they’re listening and offer a solution to concerns.

Empower Customer Service Reps

Consider these tips to ensure that your customer service representatives are equipped to handle any holiday Grinch’s phone call:

Know What to Expect. When on a call, understanding that the old measures of customer service – a cheerful greeting, friendly service, on-hold times, call times and volumes, and a wrap-up upsell pitch – no longer apply. Informed answers and expert advice are what matter most to today’s increasingly knowledgeable customers.
Provide the Training. Customer service employees must be trained. They must have all the information they possess at their fingertips, understanding the products and services without skipping a beat. A customer expects someone on the line to know exactly how to fix their problem and won’t settle for less.
Research is Key. Equally important, employees need to know what the online world is saying about our products and services and how we stack up against the competition. This prepares them to speak positively about the products while countering any false or negative information.
Technology is the Key

Instead of replacing humans with AI tools, companies should look towards other technologies to assist their customer service representatives to have the best experience while on a call. This means drowning out the din of representatives and their calls, thanks to noise-cancelling headphones. One study suggests that 89 percent of patrons will leave for a competitor after a negative customer service experience – elevating the need for concentration and noise-cancelling headphones to a critical level. This ensures that even the loudest office chatter don’t disturb conversations with loyal customers.

Additionally, as customer service workers spend extensive time on the phone, organizations should consider investing in high-quality cordless headsets. A 2015 study showed that 56 percent of corded headset users reported their productivity was negatively affected because they were restricted to their desk. Enabling your employees to freely move around their workspace while on a call provides them with the option to grab a file or consult with a colleague across the office without putting customers on hold.

The importance of the human element during a customer service call is critical to providing personalized and positive experiences. While companies may be tempted to cut corners, and invest in AI and bots, they should also remember that investing in employees, training and technology that empower employees ensures that their business (and customer satisfaction) will flourish.

One massive advantage of artificial intelligence is its potential to complete mundane tasks through intricate automation that will increase productivity. Theoretically this can even remove “boring” tasks from humans and free them up to be increasingly creative.
There are plenty of wild statements being thrown around about artificial intelligence – from a threat to our jobs to a threat to the human race as we know it. So is this all hyperbole or are the fears actually based on some facts? We investigate.

So what is artificial intelligence?
The concept of artificial intelligence is that computer systems can be used to perform tasks that would normally require a human. These can range from speech recognition and translation into different languages, all the way through to visual perception and even decision making.

Broadly speaking, anything can be considered artificial intelligence if it involves a program doing something that we would normally think would rely on the intelligence of a human. Quite how this is achieved is not the point – just the fact that it can be done, is a sign of artificial intelligence.
The different levels of artificial intelligence
Within the realm of artificial intelligence, there are different classifications. They include:

Strong Vs Weak
Strong artificial intelligence refers to the work that looks to genuinely imitate a human – and that could potentially even explain the way humans think. Few examples of this exist, currently. Then there is weak artificial intelligence, which simply aims to build systems that are able to behave in the same manner as humans but do not have the aim of thinking as humans think.

Narrow Vs General
Another classification of artificial intelligence are those that are meant to meet certain tasks, known as narrow artificial intelligence; and those designed to reason, known as general artificial intelligence.
So what are the pros and cons of artificial intelligence?

There are several advantages and disadvantages associated with the concept:

The advantages
Dealing with mundane tasks
One massive advantage of artificial intelligence is its potential to complete mundane tasks through intricate automation that will increase productivity. Theoretically this can even remove “boring” tasks from humans and free them up to be increasingly creative.

Faster decisions
Using artificial intelligence alongside cognitive technologies can help make faster decisions and carry out actions quicker.

Avoiding errors
The phrase “human error” was born because humans, naturally, make mistakes from time to time. Computers however, do not make these mistakes – that is, of course, assuming they are programmed properly. With artificial intelligence, data could be processed error-free, no matter how big the dataset might be

Taking risks on behalf of humans
With artificial intelligence, you can arguably lessen the risks you expose humans to in the name of research. Take, for example, space exploration and the Mars rover, known as Curiosity. It can travel across the landscape of Mars, exploring it and determining the best paths to take, while learning to think for itself. Using artificial intelligence in this manner could potentially lead to massive benefits in areas such as demand forecasting, medical diagnosis and oil exploration.

The disadvantages
Job losses
There is little doubt that artificial intelligence will displace many low-skilled jobs. Arguably, robots have already taken many jobs on the assembly line – but now this could extend to new levels. Take, for example, the concept of driverless cars, which could displace the need to have millions of human drivers, from taxi drivers to chauffeurs, very quickly. Of course some would argue that artificial intelligence will create more wealth than it destroys – but there is genuine risk that this will not be distributed evenly, particularly during its early expansion.

Distribution of power
Artificial intelligence carries the risk, in the minds of some, of taking control away from humans – de-humanising actions in many ways. Nations that are in possession of artificial intelligence could theoretically kill humans without needing to pull a trigger.

Lack of judgement calls
Humans can take unique circumstances and judgement calls into account when they make their decisions, something that artificial intelligence may never be able to do. One example occurred in Sydney, Australia, in 2014 when a shooting drama in the downtown area prompted people to make numerous calls to Uber in an effort to escape the area. The result was that Uber’s ride rates surged based on its supply and demand algorithm – there was no consideration involved for the circumstances in which the riders found themselves.

So is artificial intelligence really a threat?
If you think that artificial intelligence is just a futuristic, Jetsons-style image that is unlikely to ever affect humans on a mass scale then look no further than the employees of Fukoko Mutual Life Insurance in Japan. In January 2017, 34 of its employees were dismissed from their jobs because the insurer had installed a new artificial intelligence system that could read medical certificates, gather data on hospital stays and surgeries, and, in the process, save the company an estimated 140 million Yen per year in salary costs.

Indeed a World Economic Forum study in 2016 predicted that around 5.1 million jobs will be lost to artificial intelligence over the next five years alone, across 15 countries. Yet, to counter-balance this argument, looking at the same industry – insurance – there are advantages to be gained too. In February 2017, Tractable launched a system it claims could “radically transform” motor claims by simplifying the tedious manual process and helping to fight insurance fraud by flagging suspicious claims – potentially removing stress and expense from the process, leading to cost savings for companies and policyholders alike.

Clearly, artificial intelligence has massive potential advantages. The key for humans, however, will be to use their own judgement to apply it productively and ensure the “rise of the robots” doesn’t get out of hand.
Artificial intelligence (AI) is the intelligence of machines. It is about designing machines that can think. Researchers also aim at introducing an emotional aspect into them. How will it affect our lives? Read this Buzzle article for an overview of the pros and cons of artificial intelligence.


▸ With artificial intelligence, the chances of error are almost nil and greater precision and accuracy is achieved.

▸ Artificial intelligence finds applications in space exploration. Intelligent robots can be used to explore space. They are machines and hence have the ability to endure the hostile environment of the interplanetary space. They can be made to adapt in such a way that planetary atmospheres do not affect their physical state and functioning.

▸ Intelligent robots can be programmed to reach the Earth's nadirs. They can be used to dig for fuels. They can be used for mining purposes. The intelligence of machines can be harnessed for exploring the depths of oceans. These machines can be of use in overcoming the limitations that humans have.

▸ Intelligent machines can replace human beings in many areas of work. Robots can do certain laborious tasks. Painstaking activities, which have long been carried out by humans can be taken over by the robots. Owing to the intelligence programmed in them, the machines can shoulder greater responsibilities and can be programmed to manage themselves.

▸ Smartphones are a great example of the application of artificial intelligence. In utilities like predicting what a user is going to type and correcting human errors in spelling, machine intelligence is at work. Applications like Siri that act as personal assistants, GPS and Maps applications that give users the best or the shortest routes to take as well as the traffic and time estimates to reach there, use artificial intelligence. Applications on phones or computers that predict user actions and also make recommendations that suit user choice, are applications of AI. Thus, we see that artificial intelligence has made daily life a lot easier.

▸ Fraud detection in smart card-based systems is possible with the use of AI. It is also employed by financial institutions and banks to organize and manage records.

▸ Organizations use avatars that are digital assistants who interact with the users, thus saving the need of human resources.

▸ Emotions that often intercept rational thinking of a human being are not a hindrance for artificial thinkers. Lacking the emotional side, robots can think logically and take the right decisions. Sentiments are associated with moods that affect human efficiency. This is not the case with machines with artificial intelligence.

▸ Artificial intelligence can be utilized in carrying out repetitive and time-consuming tasks efficiently.

▸ Intelligent machines can be employed to do certain dangerous tasks. They can adjust their parameters such as their speed and time, and be made to act quickly, unaffected by factors that affect humans.

▸ When we play a computer game or operate a computer-controlled bot, we are in fact interacting with artificial intelligence. In a game where the computer plays as our opponent, it is with the help of AI that the machine plans the game moves in response to ours. Thus, gaming is among the most common examples of the advantages of artificial intelligence.

▸ AI is at work in the medical field too. Algorithms can help the doctors assess patients and their health risks. It can help them know the side effects that various medicines can have. Surgery simulators use machine intelligence in training medical professionals. AI can be used to simulate brain functioning, and thus prove useful in the diagnosis and treatment of neurological problems. As in case of any other field, repetitive or time-consuming tasks can be managed through the application of artificial intelligence.

▸ Robotic pets can help patients with depression and also keep them active.

Robotic radiosurgery helps achieve precision in the radiation given to tumors, thus reducing the damage to surrounding tissues.

▸ The greatest advantage of artificial intelligence is that machines do not require sleep or breaks, and are able to function without stopping. They can continuously perform the same task without getting bored or tired. When employed to carry out dangerous tasks, the risk to human health and safety is reduced.


▸ One of the main disadvantages of artificial intelligence is the cost incurred in the maintenance and repair. Programs need to be updated to suit the changing requirements, and machines need to be made smarter. In case of a breakdown, the cost of repair may be very high. Procedures to restore lost code or data may be time-consuming and costly.

▸ An important concern regarding the application of artificial intelligence is about ethics and moral values. Is it ethically correct to create replicas of human beings? Do our moral values allow us to recreate intelligence? Intelligence is a gift of nature. It may not be right to install it into a machine to make it work for our benefit.

▸ Machines may be able to store enormous amounts of data, but the storage, access, and retrieval is not as effective as in case of the human brain. They may be able to perform repetitive tasks for long, but they do not get better with experience, like humans do. They are not able to act any different from what they are programmed to do. Though this is mostly seen as an advantage, it may work the other way, when a situation demands one to act in way different from the usual. Machines may not be as efficient as humans in altering their responses depending on the changing situations.

▸ The idea of machines replacing human beings sounds wonderful. It appears to save us from all the pain. But is it really so exciting? Ideas like working wholeheartedly, with a sense of belonging, and with dedication have no existence in the world of artificial intelligence. Imagine robots working in hospitals. Do you picture them showing the care and concern that humans would? Due you think online assistants (avatars) can give the kind of service that a human being would? Concepts such as care, understanding, and togetherness cannot be understood by machines, which is why, how much ever intelligent they become, they will always lack the human touch.

▸ Imagine intelligent machines employed in creative fields. Do you think robots can excel or even compete the human mind in creative thinking or originality? Thinking machines lack a creative mind. Human beings are emotional intellectuals. They think and feel. Their feelings guide their thoughts. This is not the case with machines. The intuitive abilities that humans possess, the way humans can judge based on previous knowledge, the inherent abilities that they have, cannot be replicated by machines. Also, machines lack common sense.

▸ If robots begin to replace humans in every field, it will eventually lead to unemployment. People will be left with nothing to do. So much empty time may result in its destructive use. Thinking machines will govern all the fields and populate the positions that humans occupy, leaving thousands of people jobless.

▸ Also, due to the reduced need to use their intelligence, lateral thinking and multitasking abilities of humans may diminish. With so much assistance from machines, if humans do not need to use their thinking abilities, these abilities will gradually decline. With the heavy application of artificial intelligence, humans may become overly dependent on machines, losing their mental capacities.

▸ If the control of machines goes in the wrong hands, it may cause destruction. Machines won't think before acting. Thus, they may be programmed to do the wrong things, or for mass destruction.

▸ Apart from all these cons of AI, there is a fear of robots superseding humans. Ideally, human beings should continue to be the masters of machines. However, if things turn the other way round, the world will turn into chaos. Intelligent machines may prove to be smarter than us, they might enslave us and start ruling the world.

It should be understood that artificial intelligence has several pros but it has its disadvantages as well. Its benefits and risks should be carefully weighed before employing it for human convenience. Or, in the greed to play God, man may destroy himself.