Abstract
Artificial intelligence (AI) and machine learning promise to make major changes to the relationship of people and organizations with technology and information. However, as with any form of information processing, they are subject to the limitations of information linked to the way in which information evolves in information ecosystems. These limitations are caused by the combinatorial challenges associated with information processing, and by the tradeoffs driven by selection pressures. Analysis of the limitations explains some current difficulties with AI and machine learning and identifies the principles required to resolve the limitations when implementing AI and machine learning in organizations. Applying the same type of analysis to artificial general intelligence (AGI) highlights some key theoretical difficulties and gives some indications about the challenges of resolving them.
Highlights
The role of artificial intelligence (AI) and machine learning in organizations and society is of critical importance
Understand the levels of fitness required and their relationship with information measures; Analyze the integration challenges of different AI approaches—the requirements for delivering reliable outcomes from a range of disparate components reflecting the conventions of different information ecosystems; Understand the best way to manage ecosystems boundaries—initially, how AI and people can work together but increasingly how AI can support effective interaction across other ecosystem boundaries; Provide assurance about the impact and risks as AI becomes more prevalent and the issues discussed above become more important to organizational success
Manage each interaction and to decide how to respond—each type of interaction may require different different specific specific capabilities; capabilities; prioritize the the response response to to different different interactions interactions of of the the same same or or different different types; types; prioritize respond to environment change—this is a priority for businesses as the the world world becomes becomes respond to environment change—this is a priority for businesses as increasingly digital and the implementation of and machine learning takes hold increasingly digital and the implementation of AI and machine learning takes hold [11]
Summary
The role of artificial intelligence (AI) and machine learning in organizations and society is of critical importance. This section deals with current issues with machine learning and demonstrates a theoretical basis for implementation principles to: Understand the levels of fitness required and their relationship with information measures (like quality, friction, and pace [5,6]); Analyze the integration challenges of different AI approaches—the requirements for delivering reliable outcomes from a range of disparate components reflecting the conventions of different information ecosystems; Understand the best way to manage ecosystems boundaries—initially, how AI and people can work together but increasingly how AI can support effective interaction across other ecosystem boundaries; Provide assurance about the impact and risks as AI becomes more prevalent and the issues discussed above become more important to organizational success. When we analyze these questions, it is clear that there are difficult information theoretic problems to be overcome on the route to the successful implementation of AGI
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
