The state of AI ethics: The principles, the tools, the regulations
What do we talk about when we talk about AI ethics? Just like AI itself, definitions for AI ethics seem to abound. A definition that seems to have garnered some consensus is that AI ethics is a system of moral principles and techniques intended to inform the development and responsible use of artificial intelligence technologies.
Read More →Working from home means working different hours, but not necessarily more
The National Bureau of Economic Research analyzed the side effects of remote work using data from GitHub.
Read More →What will applied AI look like in 2022?
AI adoption has skyrocketed throughout the last 18 months. Besides Joe McKendrick, who wrote the foundational piece on HBR, professionals who work on AI would readily attest to this statement. Google search seems to be in on this not-so-secret too: When prompted with “AI adoption,” its auto-complete spurts out “skyrocketed over the last 18 months”.
Read More →2022 technology trend review, part two: AI and graphs
AI and graphs have a few things in common: they are multi-faceted, ubiquitous in their applications, and seeing rapid growth in the 2020s.
Read More →LinkedIn and Intel tech leaders on the state of AI
AI is on a roll. Adoption is increasing across the board, and organizations are already seeing tangible benefits. However, the definition of what AI is and what it can do is up for grabs, and the investment required to make it work isn’t always easy to justify. Despite AI’s newfound practicality, there’s still a long way to go.
Let’s take a tour through the past, present, and future of AI, and learn from leaders and innovators from LinkedIn, Intel Labs, and cutting-edge research institutes.
Read More →The State of AI in 2021: Language models, healthcare, ethics, and AI agnosticism
Takeaways from an action-packed 2021 for AI: Healthcare is just getting started with its AI moment, bigger language models mean bigger complications, and there may now be a third pole for AGI.
Read More →The state of AI in 2021: Machine learning in production, MLOps and data-centric AI
With lessons learned from operationalizing AI, the emphasis is shifting from shiny new models to perhaps more mundane, but practical aspects such as data quality and data pipeline management
Read More →DeepMind is developing one algorithm to rule them all
DeepMind wants to enable neural networks to emulate algorithms to get the best of both worlds, and it’s using Google Maps as a testbed.
Read More →DeepMind aims to marry deep learning and classic algorithms
Will deep learning really live up to its promise? We don’t actually know. But if it’s going to, it will have to assimilate how classical computer science algorithms work. This is what DeepMind is working on, and its success is important to the eventual uptake of neural networks in wider commercial applications.
Read More →AI ethics in the real world: FTC commissioner shows a path toward economic justice
FTC Commissioner Rebecca Kelly Slaughter lays out machine learning and AI's potential for harm and outlines some ways for the FTC to counter it.
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