Michael Abramov

The construction industry's future is not just about using more machines to replace people. It's about teaming up human skills with AI help. Despite worries that AI will take jobs away, it's been shown to boost what people can do just as well. To

AI is getting better fast and the role of farmer expertise in AI models is increasing. Our machines are already good at diagnosing diseases, translating languages, and helping customers. In farming, AI can help with collecting and analyzing data, doing tasks, and even heavy labor. This frees up farmers to

AI governance became a motto of 2024, as an estimated 42% of companies use AI. This situation opens the door for biased outcomes, heightened inequalities, and violations of individual rights. AI is particularly difficult to regulate because it touches on so many aspects of society and includes so many stakeholders.

Data annotation for AI in finance is a key challenge for unlocking value of ML models. Annotated data is essential for building AI models that are both accurate and fair for finance tasks. It allows computers to understand data like financial reports or market trends. Adding human insights to data

The increasing use of AI in our systems brings up numerous questions that span across the whole fabric of our societies. We’ve already discussed the ethical and legal implications of artificial agents in a broader sense -  this time we’ll talk about specific issues and evolving frameworks designed

Did you know that AI tech in agriculture is expected to jump from $1.1 billion in 2019 to over $3.8 billion by 2024? The rise of artificial intelligence in farming needs to be mindful of ethical issues. Though AI could change farming for the better, it raises concerns