Category:Business
Revision as of 09:43, 21 June 2022 by Dawn.Hunter (talk | contribs)
This is the page for all resources which fit into the overall theme of AI and Business.
Here you will find links to all of the resources which look at use of AI in a business context.
Pages in category "Business"
The following 54 pages are in this category, out of 54 total.
A
- A Parent and Carers Digital Careers Guide (SDS)
- Action Toolkit On Inclusive AI (Women's Forum) (2021)
- AI Activity in UK Business Executive Summary (UK Government)
- AI Adoption Assessment Toolkit (Catapult Digital)
- AI Adoption in the UK: Putting AI into Action (techUK)
- AI Business School (Microsoft)
- AI for Disability Inclusion (Accenture)
- AI in Financial Services (Alan Turing Institute)
- AI in Practice Training Programme (The AI Summit London)
- AI Index 2022 (Stanford HAI)
- AI Judicial Guidance (Courts and Tribunals Judiciary)
- AI Report 2022 - Patents at the EPO – a long-term trend analysis (Marks & Clerk)
- AI Risk Assessment Methodologies (Tri Lateral Research)
- Artificial Intelligence In Public Services (Equality and Human Rights Commission)
B
C
D
E
- EAIGG Annual Report
- Elements of AI (University of Helsinki)
- Empowering AI Leadership C Suite Toolkit (World Economic Forum)
- Enabling Responsible Access To Demographic Data To Make AI Systems Fairer (Scottish Government)
- Ethical AI Frameworks, Guidelines, Toolkits (AI Ethicist)
- Ethics of AI (University of Helsinki)
- Ethics of Artificial Intelligence (SpringerLink)
- Exploring artificial intelligence adoption in public organizations: a comparative case study
M
S
T
- Technology and Innovation Report 2023 (UNCTAD)
- The Data Ethics Canvas 2021 (ODI)
- The Ethics of AI Business Practices: A Review of 47 AI Ethics Guidelines (Montreal AI Ethics Institute)
- The NIST Artificial Intelligence Risk Management Framework (US Government)
- The strategic impacts of Intelligent Automation for knowledge and service work: An interdisciplinary review (The Journal of Strategic Information Systems, Coombs, Hislop, Taneva and Barnard) (2020)
- Towards Data Science (Library)