A Quick Guide to Robotics

What are Robotics?

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Seth Adler

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Robotics is a branch of technology that designs, develops, and deploys robots, either in a hardware or software form. Sensors and computer software within physical robots allow them to interact with their environment. Some robots are created for specific tasks and functions that humans have typically performed. 

Robotics are used in the global manufacturing sector in assembly, packaging, customer service, and sold as open source robotics where users can teach robots custom tasks. Collaborative robots—or cobots—are robots that are designed to physically interact with humans in a shared workspace. They can be valuable to organizations who wish to eliminate human participation in dirty, dull and/or dangerous tasks.

Despite not achieving human-like intelligence, there are still many successful examples of robots executing autonomous tasks, such as swimming, carrying boxes, picking up objects and putting them down.

The next evolution in robotics is to make robots as autonomous as possible through learning. Some robots can learn decision making by making an association between an action and a desired result. Kismet, a robot at MIT’s Artificial Intelligence Lab, is learning to recognize both body language and voice and how to respond appropriately.


Robotic Process Automation

Artificial intelligence is at one end of the spectrum of intelligent automation, while robotic process automation (RPA), the science of software robots that mimic human actions, is at the other. One is concerned with replicating how humans think and learn, while the other is concerned with replicating how humans do things. 

RPA also takes the form of human-mimicking software, or bots. For example, RPA software can log into IT systems, copy and paste data, create reports, and perform other rules-driven software tasks. While there is a lot of talk about robots replacing humans in the workforce, RPA’s intent is to enhance the human work experience. By automating tedious, time-consuming, and error-prone processes with RPA, the human worker is freed up to work on higher-value duties. For example, onboarding a new employee pulls a current employee from their obligations and slows down workflow. With the assistance of RPA, the onboarding process is automated and can be completed by a new hire independently. 

Because RPA includes a rules-based foundation using algorithms and programming, it is useful in sectors that must comply to regulatory mandates. As laws change, so too can RPA programs change to adopt companywide compliance rules to legacy forms, policies, and documentation.   


Listen to Martin Ruange discuss the benefits of implementing RPA into workforce processes

Source: The AI Network Podcast


RPA functions are attended, unattended, or a hybrid of the two.

  • Attended - Front office and call center tasks enjoy increased productivity and smoother transactions with RPA assistance. For example, when a human receives a customer call, an attended RPA bot can be told to pull up and auto-fill all relevant information for that caller. Less time is spent entering data manually, and that time and energy instead gets channeled into providing a customer experience of higher quality.
  • Unattended - Unattended RPA is more typically used in back-office situations. For example, a healthcare provider can use an unattended RPA tool to quickly batch and process patient records and invoices in accordance to industry regulations. Monitoring, reporting, and auditing are also streamlined through the use of unattended RPA bots.
  • Hybrid - A hybrid approach to RPA combines the speed and ease of unattended processes with the human oversight sometimes necessary in attended processes. For example, an insurance company may take advantage of a hybrid RPA model when processing claims. The act of sorting, categorizing, and streamlining claims works in an unattended way, where the decision to deny or approve a claim is a task best left to human attendance. 


RPA and IoT

Internet of Things (IoT) is the term coined to represent smart technology in the home and office. Connected devices such as the Ring, activity trackers, and smart cars fall under the IoT definition. In order to create a holistic automated environment that works together, not in silos, RPA is able to communicate across platforms, devices, and manufacturers. 

For example, if a home monitoring system detects a gas leak, that detection is flagged. Communicating the event to the homeowner is an example of RPA, because it takes the identified event and is able to translate it and communicate it to the homeowner through their connected devices in a text-based message. While it sounds simple, the complexities and demand of combining all of these technologies in a seamless way has driven—and continues to drive—RPA science and innovation forward at a rapid rate.

The Industrial Internet of Things applies specifically to the smart hardware that operates within a specific industry.  


Beyond RPA

While the time- and money-saving advantages to RPA are invaluable, without the ability to learn, RPA runs into functional issues that can halt its intended productivity. A robot can get stuck on a certain task when presented with a scenario it hasn’t been programmed for. In these cases, the robot needs to make a judgment on how to proceed.


Intelligent Process Automation (IPA)

Intelligent process automation is the term coined to describe AI and robotics working in conjunction. While neither are particularly new, the cloud, increased processing speed, and improved sensor technology is allowing for advances in these fields. For example, if a piece of IPA software is unable to perform its designated task, it can diagnose and execute its own fix—let’s say an operating system update—before carrying on with its duties. IPA also has the ability to learn from its own experiences, which allows it to improve over time without human intervention.

  • Voice/speech recognition Voice recognition, also called speech recognition, is an area of great interest in RPA and IPA. Robotic interactions are intended to be as natural and human-like as possible, which means speech plays a critical role. Understanding context and intent is a nuanced action, but natural language processing and machine learning are working i n conjunction with IPA to provide a smooth user experience. 
  • Natural language processing - As its goal is to work side by side with and learn from human intelligence, cognitive systems must be able to understand human speech and written text. Natural language processing (NLP) is the area of computer science concerned with this. IPA systems can receive, understand, interpret, and offer feedback in written and spoken forms that emulate human syntax. Although this feat is incredibly difficult given the considerable variances in human communication, NLP technology is advancing at a rapid rate. NLP is responsible for predictive text, Google’s ability to guess search parameters, communications with Siri and Alexa, and natural-sounding chatbots
  • Machine learning - ML uses neural networks, a computer system modeled after how the human brain processes information. It is an algorithm designed to recognize patterns, calculate the probability of a certain outcome occurring, and “learn” through error and successes using a feedback loop. Machine learning is the branch of artificial intelligence that transforms RPA into IPA. 

In the banking industry, IPA can spot certain trends within its customer data and act on those trends by suggesting products that fit that customer profile’s behavior. For example, an IPA can spot a client who is likely to soon be buying a home, because it not only sorts client data, but it learns the patterns and outcomes of that data. Then, the IPA can suggest a mortgage option that fits that particular customer—all before the client even asks. 

Customer requests can be streamlined and automated with the use of IPA and natural language processors (NLP). When a customer calls or utilizes a chat bot, the IPA has the ability to solve the client’s request quickly and accurately. If it hits a dead end, once human intervention successfully carries out the event, IPA learns from this and is better informed going forward. 


IPA in the business sector

Early adopters of IPA are already reaping the benefits. McKinsey reported that many of the companies who have adopted IPA are already reaping the rewards. The report also suggests that these companies have automated upwards of 70% of their tasks and enjoyed an ROI above 100%. In the future, large corporations may find it difficult to keep up with their competitors if they don’t also onboard IPA technology.  

  • Intelligent enterprise - Technology has enabled a new global consumer and enterprise landscape. Corporations are becoming increasingly more complex, as different cultures, languages, and processes now exist under one umbrella. Back office applications contain more data than a human staff can manage. That is why intelligent enterprise and a digital workforce is becoming a must-have for corporations to remain competitive. The intelligent enterprise utilizes data, RPA, IPA, and new innovations in order to streamline their processes, reduce overhead, and improve customer service. 
  • Digital transformation - Digital transformation utilizes new technologies such as subscription-based cloud services. IPA services include expense reporting, internal onboarding and offboarding, and document generation. These tasks that were once so labor intensive when done by hand are now nearly invisible and provide a smooth experience for frontend and backend users at a decreased cost to the corporation. 


This webinar weighs up the benefits and risks of pressing forward with robotics

Source: AIIA.net: AI and Intelligent Automation


The Future of robotics, RPA, and IPA

Increasingly, robotics is focusing on progressing its efforts to create more lifelike robots, bots, and software. The intent is to streamline bots into our lives in a more natural and widely accepted way as coworkers, teachers, and customer service representatives. While the majority of the tasks robotics aims to replace is backend, tedious work, an inevitable side effect of these cost saving, time saving technologies is the loss of jobs. However, robotics also offers new and exciting industry sectors and in-demand skillsets. Forward-thinking companies and universities are currently reskilling and shifting curriculum toward the workforce of the future.   


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