Editing Automation (section)

== Advantages, disadvantages, and limitations ==

Perhaps the most cited advantage of automation in industry is that it is associated with faster production and cheaper labor costs. Another benefit could be that it replaces hard, physical, or monotonous work.<ref>{{Cite book|title = Industrial Automation: Hands on|last = Lamb|first = Frank|year = 2013|pages = 1–4}}</ref> Additionally, tasks that take place in [[Occupational hazard|hazardous environments]] or that are otherwise beyond human capabilities can be done by machines, as machines can operate even under extreme temperatures or in atmospheres that are radioactive or toxic. They can also be maintained with simple quality checks. However, at the time being, not all tasks can be automated, and some tasks are more expensive to automate than others. Initial costs of installing the machinery in factory settings are high, and failure to maintain a system could result in the loss of the product itself.

Moreover, some studies seem to indicate that industrial automation could impose ill effects beyond operational concerns, including worker displacement due to systemic loss of employment and compounded environmental damage; however, these findings are both convoluted and controversial in nature, and could potentially be circumvented.<ref>{{Cite news|title=The Risk of Automation for Jobs in OECD Countries: A COMPARATIVE ANALYSIS|last=Arnzt|first=Melanie|date=14 May 2016|id = {{ProQuest|1790436902}}}}</ref>

The main '''advantages''' of automation are:
*Increased throughput or productivity
*Improved quality
*Increased [[predictability]]
*Improved [[robustness]] (consistency), of processes or product
*Increased consistency of output
*Reduced direct human labor costs and expenses
*Reduced [[cycle time variation|cycle time]]
*Increased accuracy
*Relieving humans of monotonously repetitive work<ref>{{Cite web|url=http://www.bma-automation.com/Prozessautomatisierung.2102.0.html?id=2102&L=1|archive-url=https://web.archive.org/web/20130517174600/http://www.bma-automation.com/Prozessautomatisierung.2102.0.html?id=2102&L=1|title=Process automation, retrieved on 20.02.2010|archive-date=17 May 2013}}</ref>
*Required work in development, deployment, maintenance, and operation of automated processes — often structured as "jobs"
*Increased human freedom to do other things

Automation primarily describes machines replacing human action, but it is also loosely associated with mechanization, machines replacing human labor. Coupled with mechanization, extending human capabilities in terms of size, strength, speed, endurance, visual range & acuity, hearing frequency & precision, electromagnetic sensing & effecting, etc., advantages include:<ref>Bartelt, Terry. Industrial Automated Systems: Instrumentation and Motion Control. Cengage Learning, 2010.</ref>
*Relieving humans of dangerous work stresses and [[occupational injuries]] (e.g., fewer strained backs from lifting heavy objects)
*Removing humans from dangerous environments (e.g. fire, space, volcanoes, nuclear facilities, underwater, etc.)

The main '''disadvantages''' of automation are:
*High initial cost
*Faster production without human intervention can mean faster unchecked production of defects where automated processes are defective.
*Scaled-up capacities can mean scaled-up problems when systems fail — releasing dangerous toxins, forces, energies, etc., at scaled-up rates.
*Human adaptiveness is often poorly understood by automation initiators. It is often difficult to anticipate every contingency and develop fully preplanned automated responses for every situation. The discoveries inherent in automating processes can require unanticipated iterations to resolve, causing unanticipated costs and delays.
*People anticipating employment income may be seriously disrupted by others deploying automation where no similar income is readily available.

=== Paradox of automation ===
The [[paradox]] of automation says that the more efficient the automated system, the more crucial the human contribution of the operators. Humans are less involved, but their involvement becomes more critical. [[Lisanne Bainbridge]], a cognitive psychologist, identified these issues notably in her widely cited paper "Ironies of Automation."<ref>{{Cite journal|last=Bainbridge|first=Lisanne|date=November 1983|title=Ironies of automation|journal=Automatica|volume=19|issue=6|pages=775–779|doi=10.1016/0005-1098(83)90046-8|s2cid=12667742 }}</ref> If an automated system has an error, it will multiply that error until it is fixed or shut down. This is where human operators come in.<ref>{{cite web|last=Kaufman|first=Josh|title=Paradox of Automation – The Personal MBA|url=http://personalmba.com/paradox-of-automation/|website=Personalmba.com}}</ref> A fatal example of this was [[Air France Flight 447]], where a failure of automation put the pilots into a manual situation they were not prepared for.<ref>{{cite web|title=Children of the Magenta (Automation Paradox, pt. 1) – 99% Invisible|url=http://99percentinvisible.org/episode/children-of-the-magenta-automation-paradox-pt-1/|website=99percentinvisible.org|date=23 June 2015 }}</ref>

===Limitations===
{{Unreferenced section|date=May 2019}}
* Current technology is unable to automate all the desired tasks.
* Many operations using automation have large amounts of invested capital and produce high volumes of products, making malfunctions extremely costly and potentially hazardous. Therefore, some personnel is needed to ensure that the entire system functions properly and that safety and product quality are maintained.<ref>{{cite book |title=Artificial Intelligence and Robotics and Their Impact on the Workplace |url=https://www.ibanet.org/Document/Default.aspx?DocumentUid=c06aa1a3-d355-4866-beda-9a3a8779ba6e}}</ref>
* As a process becomes increasingly automated, there is less and less labor to be saved or quality improvement to be gained. This is an example of both [[diminishing returns]] and the [[logistic function]].
* As more and more processes become automated, there are fewer remaining non-automated processes. This is an example of the exhaustion of opportunities. New technological paradigms may, however, set new limits that surpass the previous limits.

====Current limitations====
Many roles for humans in industrial processes presently lie beyond the scope of automation. Human-level [[pattern recognition]], [[language comprehension]], and language production ability are well beyond the capabilities of modern mechanical and computer systems (but see ''[[Watson computer]]''). Tasks requiring subjective assessment or synthesis of complex sensory data, such as scents and sounds, as well as high-level tasks such as strategic planning, currently require human expertise. In many cases, the use of humans is more [[cost-effective]] than mechanical approaches even where the automation of industrial tasks is possible. Therefore, [[algorithmic management]] as the digital rationalization of human labor instead of its substitution has emerged as an alternative technological strategy.<ref>{{Cite journal |last=Schaupp |first=Simon |date=2022-05-23 |title=COVID-19, economic crises and digitalisation: How algorithmic management became an alternative to automation |journal=New Technology, Work and Employment |volume=38 |issue=2 |language=en |pages=311–329 |doi=10.1111/ntwe.12246 |issn=0268-1072 |pmc=9347406 |pmid=35936383}}</ref> Overcoming these obstacles is a theorized path to [[post-scarcity]] economics.<ref>{{Cite book |last=Benanav |first=Aaron |title=Automation and the future of work |date=2020 |isbn=978-1-83976-129-4 |location=London |publisher=Verso |oclc=1147891672}}</ref>

===Societal impact and unemployment===
{{main|Technological unemployment}}

Increased automation often causes workers to feel anxious about losing their jobs as technology renders their skills or experience unnecessary. Early in the [[Industrial Revolution]], when inventions like the [[steam engine]] were making some job categories expendable, workers forcefully resisted these changes. [[Luddites]], for instance, were English [[Textile manufacturing|textile workers]] who protested the introduction of [[weaving machines]] by destroying them.<ref>{{cite web|url=https://www.britannica.com/event/Luddite|title=Luddite|website=Encyclopedia Britannica|access-date=28 December 2017}}</ref> More recently, some residents of [[Chandler, Arizona]], have slashed tires and pelted rocks at [[self-driving car]], in protest over the cars' perceived threat to human safety and job prospects.<ref>{{cite news |last= Romero|first= Simon|date= 31 December 2018|title= Wielding Rocks and Knives, Arizonans Attack Self-Driving Cars|url= https://www.nytimes.com/2018/12/31/us/waymo-self-driving-cars-arizona-attacks.html|work= The New York Times}}</ref>

The relative anxiety about automation reflected in opinion polls seems to correlate closely with the strength of [[organized labor]] in that region or nation. For example, while a study by the [[Pew Research Center]] indicated that 72% of Americans are worried about increasing automation in the workplace, 80% of Swedes see automation and [[artificial intelligence]] (AI) as a good thing, due to the country's still-powerful unions and a more robust national [[Social safety net|safety net]].<ref>{{cite news|url=https://www.nytimes.com/2017/12/27/business/the-robots-are-coming-and-sweden-is-fine.html|title=The Robots are Coming, and Sweden is Fine|last=Goodman|first=Peter S.|work=The New York Times|date=27 December 2017}}</ref>

According to one estimate, 47% of all current jobs in the US have the potential to be fully automated by 2033.<ref name=":5" /> Furthermore, wages and educational attainment appear to be strongly negatively correlated with an occupation's risk of being automated.<ref name=":5">{{cite news|url=http://www.oxfordmartin.ox.ac.uk/downloads/academic/The_Future_of_Employment.pdf|title=THE FUTURE OF EMPLOYMENT: HOW SUSCEPTIBLE ARE JOBS TO COMPUTERISATION?|last1=Frey|first1=C. B.|last2=Osborne|first2=M.A.|date=17 September 2013}}</ref> [[Erik Brynjolfsson]] and [[Andrew McAfee]] argue that "there's never been a better time to be a worker with special skills or the right education, because these people can use technology to create and capture value. However, there's never been a worse time to be a worker with only 'ordinary' skills and abilities to offer, because computers, robots, and other digital technologies are acquiring these skills and abilities at an extraordinary rate."<ref>{{Cite book |last=Brynjolfsson |first=Erik |title=The second machine age: work, progress, and prosperity in a time of brilliant technologies |date=2014 |others=Andrew McAfee |isbn=978-0-393-23935-5 |edition=First |location=New York |publisher=W. W. Norton |oclc=867423744}}</ref> Others however argue that highly skilled professional jobs like a [[lawyer]], [[doctor (title)|doctor]], [[engineer]], [[journalist]] are also at risk of automation.<ref>{{Cite journal |last1=Susskind |first1=Richard |last2=Susskind |first2=Daniel |date=11 October 2016 |title=Technology Will Replace Many Doctors, Lawyers, and Other Professionals |url=https://hbr.org/2016/10/robots-will-replace-doctors-lawyers-and-other-professionals |journal=Harvard Business Review}}</ref>

According to a 2020 study in the ''[[Journal of Political Economy]]'', automation has robust negative effects on employment and wages: "One more robot per thousand workers reduces the employment-to-population ratio by 0.2 percentage points and wages by 0.42%."<ref>{{Cite journal |last1=Acemoglu |first1=Daron |last2=Restrepo |first2=Pascual |s2cid=201370532 |date=2020 |title=Robots and Jobs: Evidence from US Labor Markets |journal=Journal of Political Economy |volume=128 |issue=6 |pages=2188–2244 |doi=10.1086/705716 |issn=0022-3808 |url=http://www.nber.org/papers/w23285.pdf |hdl=1721.1/130324 |hdl-access=free}}</ref> A 2025 study in the ''[[American Economic Journal]]'' found that the introduction of industrial robots reduced 1993 and 2014 led to reduced employment of men and women by 3.7 and 1.6 percentage points.<ref>{{Cite journal |last=Lerch |first=Benjamin |date=2025 |title=From Blue- to Steel-Collar Jobs: The Decline in Employment Gaps? |url=http://doc.rero.ch/record/330892/files/wp2102.pdf |journal=American Economic Journal: Macroeconomics |language=en |volume=17 |issue=1 |pages=126–160 |doi=10.1257/mac.20220051 |issn=1945-7707}}</ref>

Research by [[Carl Benedikt Frey]] and Michael Osborne of the [[Oxford Martin School]] argued that employees engaged in "tasks following well-defined procedures that can easily be performed by sophisticated algorithms" are at risk of displacement, and 47% of jobs in the US were at risk. The study, released as a [[working paper]] in 2013 and published in 2017, predicted that automation would put low-paid physical occupations most at risk, by surveying a group of colleagues on their opinions.<ref name="OMS913">{{cite web|author1=Carl Benedikt Frey|author2=Michael Osborne|date=September 2013|title=The Future of Employment: How susceptible are jobs to computerisation?|url=http://www.oxfordmartin.ox.ac.uk/publications/view/1314|publisher=[[Oxford Martin School]]|format=publication}}</ref> However, according to a study published in ''[[McKinsey Quarterly]]''<ref name="MKQ1115">{{cite magazine |author=Chui, Michael |author2=James Manyika |author3=Mehdi Miremadi |date=November 2015 |title=Four fundamentals of workplace automation |url=http://www.mckinsey.com//Insights/Business_Technology/Four_fundamentals_of_workplace_automation |archive-url=https://web.archive.org/web/20151107195208/http://www.mckinsey.com//Insights/Business_Technology/Four_fundamentals_of_workplace_automation |archive-date=2015-11-07 |magazine=[[McKinsey Quarterly]] |quote=Very few occupations will be automated in their entirety in the near or medium term. Rather, certain activities are more likely to be automated....}}</ref> in 2015 the impact of computerization in most cases is not the replacement of employees but the automation of portions of the tasks they perform.<ref name="NYT11615">{{cite news|author1=Steve Lohr|date=6 November 2015|title=Automation Will Change Jobs More Than Kill Them|work=The New York Times|url=http://bits.blogs.nytimes.com/2015/11/06/automation-will-change-jobs-more-than-kill-them/|quote=technology-driven automation will affect almost every occupation and can change work, according to new research from McKinsey}}</ref> The [[methodology]] of the McKinsey study has been heavily criticized for being intransparent and relying on subjective assessments.<ref>{{Cite journal|last=Arntz er al|date=Summer 2017|title=Future of work|journal=Economic Lettets}}</ref> The methodology of Frey and Osborne has been subjected to criticism, as lacking evidence, historical awareness, or credible methodology.<ref>{{cite journal|last1=Autor|first1=David H.|year=2015|title=Why Are There Still So Many Jobs? The History and Future of Workplace Automation|url=https://dspace.mit.edu/bitstream/1721.1/109476/1/Autor_Why%20are%20there.pdf|journal=Journal of Economic Perspectives|volume=29|issue=3|pages=3–30|doi=10.1257/jep.29.3.3|hdl=1721.1/109476|doi-access=free}}</ref><ref>{{cite SSRN |last1=McGaughey |first1=Ewan |date=10 January 2018 |title=Will Robots Automate Your Job Away? Full Employment, Basic Income, and Economic Democracy |ssrn=3044448}}</ref> Additionally, the Organisation for Economic Co-operation and Development ([[OECD]]) found that across the 21 OECD countries, 9% of jobs are automatable.<ref>{{cite journal |author=Arntzi, Melanie |author2=Terry Gregoryi |author3=Ulrich Zierahni |year=2016 |title=The Risk of Automation for Jobs in OECD Countries |journal=OECD Social, Employment and Migration Working Papers |issue=189 |doi=10.1787/5jlz9h56dvq7-en |doi-access=free}}</ref>

Based on a formula by [[Gilles Saint-Paul]], an economist at [[Toulouse 1 University Capitole|Toulouse 1 University]], the demand for unskilled human capital declines at a slower rate than the demand for skilled human capital increases.<ref>{{cite book|last1=Saint-Paul|first1=Gilles|title=Innovation and Inequality: How Does Technical Progress Affect Workers?|date=21 July 2008|publisher=Princeton University Press |isbn=978-0-691-12830-6}}</ref> In the long run and for society as a whole it has led to cheaper products, [[Working time#Gradual decrease|lower average work hours]], and new industries forming (i.e., robotics industries, computer industries, design industries). These new industries provide many high salary skill-based jobs to the economy. By 2030, between 3 and 14 percent of the global workforce will be forced to switch job categories due to automation eliminating jobs in an entire sector. While the number of jobs lost to automation is often offset by jobs gained from technological advances, the same type of job loss is not the same one replaced and that leading to increasing unemployment in the lower-middle class. This occurs largely in the US and developed countries where technological advances contribute to higher demand for highly skilled labor but demand for middle-wage labor continues to fall. Economists call this trend "income polarization" where unskilled labor wages are driven down and skilled labor is driven up and it is predicted to continue in developed economies.<ref>{{cite book|author=McKinsey Global Institute|url=https://www.mckinsey.com/~/media/McKinsey/Global%20Themes/Future%20of%20Organizations/What%20the%20future%20of%20work%20will%20mean%20for%20jobs%20skills%20and%20wages/MGI-Jobs-Lost-Jobs-Gained-Report-December-6-2017.ashx|title=Jobs Lost, Jobs Gained: Workforce Transitions in a Time of Automation|date=December 2017|publisher=Mckinsey & Company|pages=1–20}}</ref>