Cryptoeconomics in the press
AI is replacing more of women's jobs, but can we build inclusive workplaces?
A study by professor Catherine Tucker and co-author found that job advertisements in STEM (Science, Technology, Engineering and Mathematics) were shown more frequently to men than women, even when advertisers aimed for equal exposure. The advertisement was shown in 191 countries to men and women over the age of 18.
AI is changing the nature of ads on the internet
Professor Catherine Tucker said: "AI allows content or format to actually, potentially, really resonate for the person who's seeing the ad."
Artificial intelligence and algorithmic exclusion
Professor Catherine Tucker wrote: "AI systems can fail not only because they make biased predictions, but also because they make no meaningful predictions at all for certain individuals or populations. That is, unfairness may arise not only because an algorithm sees individuals incorrectly, but also because it does not see them at all when it tries to make real-time predictions."
Algorithmic exclusion harming AI ability to make successful predictions
"Algorithmic exclusion occurs when algorithms are unable to even make predictions because they lack the data to so."
Blockchain for marketing? Maybe, but privacy issues abound
"The risk is that companies will use blockchain methods to record transactions without even caring whether the information ... is true."
MIT Professor believes DeFi can reduce banking power: Interview
“Banking tends to be unusually concentrated ... Decentralised finance as a movement promises to change this pattern of concentration.”
What blockchain can’t do
Blockchain can’t ensure that perhaps the most important step of verification is happening correctly.
A slice of pizza for your most intimate secrets? How much (or little) we value our digital privacy
Christian Catalini says: "...although we do care about privacy, we make rushed or impulsive decisions when placed in the wrong context."
How blockchain applications will move beyond finance
Christian Catalini writes: "As cryptocurrencies like bitcoin and distributed ledgers continue to mature, where might they be applied next?"
News on Cryptoeconomics
Where to look for generative AI risks
New research can help business leaders identify and address AI components that introduce risk, such as training data, foundation models, and user prompts.
This new framework helps companies build secure AI systems
New guidance includes 10 questions that can help organizations build secure-by-design artificial intelligence.
Machine learning and generative AI in 2025
While generative AI is widely accessible and useful, businesses need to know when to use other AI tools, like traditional machine learning.
How organizations build a culture of AI ethics
From risk management policies to the five stages of AI ethics, here’s how some organizations approach ethical AI.
What leaders should know about ’bring your own AI’
Companies need a plan for when employees use unapproved, publicly accessible generative artificial intelligence tools for work-related tasks.
Bringing transparency to the data used to train AI
Using the wrong datasets to train AI models can result in legal risks, bias, or lower-quality models. The Data Provenance Initiative’s tool can help.
4 ways that AI and tech are reshaping finance
Generative AI and financial data are opening up the digital economy to more consumers and small businesses, but crypto concerns remain.
5 cybersecurity priorities that demand your attention
Security leaders must strengthen their defenses against everyday threats while preparing for potentially devastating attacks. Here’s how to get it done.
How to manage two types of generative AI
Businesses have identified two types of generative AI: broadly applicable tools that boost personal productivity, and tailored solutions for specific purposes.
New database details AI risks
The AI Risk Repository, a database of over 700 risks posed by AI, aims to provide a shared framework for monitoring and maintaining AI risk oversight.