Towards the Future of Work: Managing the Risks of AI and Automation
Many believe in a vision of the future where almost all work is automated. A first step already underway involves Robotic Process Automation (RPA) technology, which firms use to automate standardized computer work. The larger step that needs to be taken towards this vision lies in connecting RPA to...
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| Format: | Thesis |
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Massachusetts Institute of Technology
2022
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| Online Access: | https://hdl.handle.net/1721.1/146654 |
| _version_ | 1826202578243813376 |
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| author | Man, James |
| author2 | Sastry, Anjali |
| author_facet | Sastry, Anjali Man, James |
| author_sort | Man, James |
| collection | MIT |
| description | Many believe in a vision of the future where almost all work is automated. A first step already underway involves Robotic Process Automation (RPA) technology, which firms use to automate standardized computer work. The larger step that needs to be taken towards this vision lies in connecting RPA to AI, so that Machine Learning (ML) algorithms can be used to automate human “intelligence” and decision making in companies.
Management research surrounding the concept of Intelligent Automation (IA) is nascent and spans multiple domains. This thesis consolidatesthe fragmented research landscape through a Systematic Literature Review to address four research questions: 1) What use cases are IA fulfilling? 2) Which ML algorithms and technologies are employed? 3) What risks are associated with IA? and 4) What risk mitigation techniques are there? The findings paint a picture of what is needed to advance the value that IA delivers to firms and shore up professional practices.
Results show that the bulk (66%) of cases centered on document processing and chatbots. ML models, tended to be uninterpretable, posing transparency and risk challenges. The systematic coding of 77 key sources yielded 36 risks that fell into eight clusters that are explored in depth. Corresponding risk mitigation measures covered far less ground, leaving many risks unaddressed. The risk registry derived in this thesis offers a starting point for a structured approach to managing emergent risks necessary for IA to deliver on its promise to improve work. |
| first_indexed | 2024-09-23T12:09:50Z |
| format | Thesis |
| id | mit-1721.1/146654 |
| institution | Massachusetts Institute of Technology |
| last_indexed | 2024-09-23T12:09:50Z |
| publishDate | 2022 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/1466542022-12-01T03:25:41Z Towards the Future of Work: Managing the Risks of AI and Automation Man, James Sastry, Anjali Sloan School of Management Many believe in a vision of the future where almost all work is automated. A first step already underway involves Robotic Process Automation (RPA) technology, which firms use to automate standardized computer work. The larger step that needs to be taken towards this vision lies in connecting RPA to AI, so that Machine Learning (ML) algorithms can be used to automate human “intelligence” and decision making in companies. Management research surrounding the concept of Intelligent Automation (IA) is nascent and spans multiple domains. This thesis consolidatesthe fragmented research landscape through a Systematic Literature Review to address four research questions: 1) What use cases are IA fulfilling? 2) Which ML algorithms and technologies are employed? 3) What risks are associated with IA? and 4) What risk mitigation techniques are there? The findings paint a picture of what is needed to advance the value that IA delivers to firms and shore up professional practices. Results show that the bulk (66%) of cases centered on document processing and chatbots. ML models, tended to be uninterpretable, posing transparency and risk challenges. The systematic coding of 77 key sources yielded 36 risks that fell into eight clusters that are explored in depth. Corresponding risk mitigation measures covered far less ground, leaving many risks unaddressed. The risk registry derived in this thesis offers a starting point for a structured approach to managing emergent risks necessary for IA to deliver on its promise to improve work. S.M. 2022-11-30T19:39:16Z 2022-11-30T19:39:16Z 2022-05 2022-08-25T19:15:36.477Z Thesis https://hdl.handle.net/1721.1/146654 In Copyright - Educational Use Permitted Copyright retained by author(s) https://rightsstatements.org/page/InC-EDU/1.0/ application/pdf Massachusetts Institute of Technology |
| spellingShingle | Man, James Towards the Future of Work: Managing the Risks of AI and Automation |
| title | Towards the Future of Work: Managing the Risks of AI and
Automation |
| title_full | Towards the Future of Work: Managing the Risks of AI and
Automation |
| title_fullStr | Towards the Future of Work: Managing the Risks of AI and
Automation |
| title_full_unstemmed | Towards the Future of Work: Managing the Risks of AI and
Automation |
| title_short | Towards the Future of Work: Managing the Risks of AI and
Automation |
| title_sort | towards the future of work managing the risks of ai and automation |
| url | https://hdl.handle.net/1721.1/146654 |
| work_keys_str_mv | AT manjames towardsthefutureofworkmanagingtherisksofaiandautomation |