AI management systems: What businesses need to know
With the risks and complexity of AI, it’s important to have robust governance mechanisms. AI management systems play a crucial role in the development and deployment of AI technologies.
The potential benefits and risks of AI are formidable, for society as well as for companies. Standards that enhance transparency, data quality, and system reliability are a way to mitigate risks and maximize rewards. Incorporating desired societal and ethical outcomes based on comprehensive stakeholder inputs, they can help bridge gaps in regulation.
Insights
Artificial intelligence: What it is, how it works and why it matters
For those unfamiliar with computer science, it can be overwhelming to try and grasp the many facets of artificial intelligence and their implications. Here, we break down what artificial intelligence is, how it works, the difference between machine learning, deep learning, natural language processing and more.
Machine learning (ML): All there is to know
Learning new skills – once perceived as something reserved for humans and other intelligent sentient creatures – is now entering the realm of computer science. ML, a subfield of AI, is a key component in the world of tomorrow.
Top standards
Framework for Artificial Intelligence (AI) Systems Using Machine Learning (ML)
Information technology — Artificial intelligence — Guidance on risk management
Information technology — Artificial intelligence — Management system
Information technology — Governance of IT — Governance implications of the use of artificial intelligence by organizations