Depending on who you talk to, artificial intelligence (AI) and automation are either a godsend or a curse. They will either be the salvation of humanity or will lead us into a dystopian future, where machines and robots replace humans for everything.
The movie “I, Robot” highlighted some of the common fears that AI and automation may elicit. Robots took care of more and more functions such as cooking, cleaning houses, driving, garbage collection, and more. Eventually, a vast AI hive mind computes that humans are unnecessary and need to be killed.
An alternative future is posed by the movie “Surrogates,” where humans sit in their rooms plugged into a computer and run a robotic version of themselves in a world where there are no consequences. Suddenly people start turning up dead, and this brave new world shows its dark side.
But such visions miss the mark. For one thing, science fiction usually exaggerates the advances made in technology. By this time, we were supposed to all be driving flying cars, teleporting from one planet to another, and colonizing the galaxy. Instead, we are still taking baby steps in space flight.
AI, then, is getting there slowly. And automation is largely joined at the hip. Let’s look at what they both are, how they relate, and how they are different.
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What is Artificial Intelligence?
Encyclopedia Britannica defines artificial intelligence as: “The ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings. The term is frequently applied to the project of developing systems endowed with the intellectual processes characteristic of humans, such as the ability to reason, discover meaning, generalize, or learn from past experience.”
Massive amounts of work has been done over many decades to bring AI up to speed. Computers can be programmed to carry out complex tasks. They can even play chess well enough to beat a grandmaster at times. But, that is based on a very limited 8-by-8 square board over two dimensions.
Despite what have been regarded as colossal advances in processing speeds and memory, AI can’t match the flexibility of humans across a wider zone of activity. But when narrowed down to specific areas, AI has led to significant gains in areas such as search engines, handwriting recognition, e-commerce, computer vision, cybersecurity, and even some kinds of advanced medical diagnosis.
What is Automation?
Encyclopedia Britannica also has a definition for automation: “Application of machines to tasks once performed by human beings or, increasingly, to tasks that would otherwise be impossible. Although the term mechanization is often used to refer to the simple replacement of human labor by machines, automation generally implies the integration of machines into a self-governing system. Automation has revolutionized those areas in which it has been introduced, and there is scarcely an aspect of modern life that has been unaffected by it.”
Humans have been protesting automation since the early days of the industrial revolution. The Luddites, for example, were a secret oath-based organization of English textile workers in the early 19th century. Believing modern cotton and woolen milling machines were threatening their jobs – an early form or automation they took it upon themselves to destroy the machinery. Still, progress moved on relentlessly.
The automotive industry represented another major jump in automation with the advent of automatic devices and controls set up in mechanized production lines. They either augmented or replaced the human-centric assembly lines instituted early by Henry Ford. Essentially, automation deals with using machines to replace humans in a mechanical, electrical, or computerized capacity. Preprogrammed commands are used to control the execution of certain tasks without human intervention.
Automation today is very much part of everyday life. Traffic signals, warehouses (picking, shipping, and inventorying), and even the driving of cars and planes include major elements of automation.
How Does AI Fit in With Automation?
Edwin Pahk, vice president of growth at Aquant, sees AI as the most natural evolution to traditional automation that we’ve seen over the past couple of decades. He added that automation is a machine executing a series of instructions — exclusively set by humans — to complete a task faster and more efficiently. If an action isn’t explicitly described in the instructions, the machine can’t do it. With AI, however, the machine can take broad rules outlined by humans and determine its own pathways to success.
Elaine Lee, principal data scientist at Mimecast, goes as far as to say that artificial intelligence is an umbrella term that captures various facets of automated tasks, from machine learning to deep learning.
“The applied integration of these AI-enabled tools empowers organizations to streamline workflows, reduce human error, and enhance operational efficiency,” she said. “By mimicking human intuition, AI is helping to prevent and mitigate cyberthreats more effectively while alleviating the burden from understaffed cybersecurity teams.”
How Can AI Be Used to Enhance Automation?
One of the primary goals of AI, then, is to drive automation. AI can enhance automation in ways such as generating faster and more personalized processes, greater use and accuracy in data, and improvements in overall customer experience.
“AI can help organizations build, manage, and maintain the access model (which identity can access what), automate life cycle processes, and reduce/eliminate the need for traditional certifications,” said Rick Wagner, senior director of product management at SailPoint.
Wagner lists several ways AI can be used to enhance automation. Learning is a major one. AI can be harnessed to help automation systems learn:
- On-boarding patterns for applications.
- Commonalities among identities and applications/entitlements to automate creating business and technical roles.
- Responses from stakeholder decisions, such as approvals for access request, to suggest policy changes to improve efficiency.
- Account patterns to suggest provisioning policies.
While automation existed prior to the development of AI-enabled tools, in computing in particular, the two are now often used in tandem to maximize protection within a complex threat landscape.
Remember that automation software is designed to follow preprogrammed rules and alleviate humans from needing to complete routine, error-prone tasks. In turn, they can focus on other responsibilities of their roles that are more complex, require more attention to detail, and have a more direct effect on the security posture of their organization.
“AI can take automated tasks to the next level by analyzing data associated with that task, thus providing actionable insights on specific anomalies in near real-time,” said Lee. “In the case of advanced email and collaboration security, AI can be applied to automated tasks to analyze language cues to flag threats in email and warn users of a potential network breach.”
Also see: The History of Artificial Intelligence
AI Applications That Don’t Link With Automation
AI doesn’t have to be wrapped up in automation. There are a variety of AI applications that have little or no relation to automation.
“AI applications, like Siri and Alexa, involve a machine exhibiting and practicing something similar to what we describe as human thinking,” said Pahk. “These systems do not have a link to automation.”
On the other side of the coin, there are plenty of automation functions that have no relation to AI and no need for any kind of AI input. For example, there are a great many modes of automation that are fixed solely on repetitive, instructive tasks. After a job is performed, the system thinks no further.
One example of an automated system that does not use AI is when companies use an automated system to generate emails to customers. Traffic lights are automated and clearly have no input from AI. Otherwise, so many drivers would not waste so many hours waiting at red lights where there were no cars coming the other way.
But Wagner believes this is changing. As AI matures and the price of systems reduces, it is finding its way into all kinds of areas, even mundane areas like traffic lights. Expect AI-based traffic lights at some time over the next few years to achieve some kind of broad implementation. In most computing examples, AI is very much tied into automation.
“A direct way is through the analysis of identities, accounts, and entitlements to recommend different types of roles and access profiles,” said Wagner. “An indirect method is learning patterns of responses for access requests to suggest a change in policy, which may indicate that approval is always completed and therefore can be changed to automate the access.”
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Are AI and Automation a Threat to Jobs?
Yes, and no. We may see some kind of anti-automation movement take shape, as certain areas will be severely impacted. But ultimately, innovation tends to make certain types of work obsolete while it opens up new vistas of job opportunity.
A Media & Technology Survey by the Communication Research Center (CRC) at Boston University’s College of Communication, in partnership with market research firm Ipsos, asked about the threat of AI. Participants were directly asked their opinions about AI replacing humans in jobs such as journalist, spiritual adviser, hiring manager, trial judge, and leader of a religious congregation.
The findings? More young people than old, and more men than women (by about 10%) turned out to be open to artificial intelligence-powered machines replacing people in a variety of jobs. By more than 30%, Americans ages 18 to 34 were more receptive than those 55 or older when considering AI replacing people in all of those job types listed.
Yet there is still fear present. Three out of four respondents across all ages, genders, ethnicities, and income groups said that having AI replace people in these jobs “doesn’t seem like a good idea” or is “definitely a bad idea.” One quarter says it’s definitely or probably a good idea.
Let’s see what the future holds.
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