Because of the extensive use of technology, and the division of labour, the work of the average gig economy worker has lost all individual character, and, consequently, all charm for the employee.
In the light of the ongoing climate crisis, let’s talk about the carbon footprint of artificial intelligence. The everyday internet user might find it hard to fathom the fact that using ChatGPT or watching YouTube-recommended videos might generate greenhouse emissions. And, understandably, they could be least concerned about “Green AI” or “Environmental AI” when using these technologies. But for researchers and data scientists, the carbon footprint created as a result of the machines, computers, and digital devices being powered by machine learning (ML) – is a growing concern, especially as global climatic change continues to escalate.
In 2009, Hal Varian, Google Chief Economist, was quoted as saying to the McKinsey Quarterly: “The sexiest job in the next 10 years will be statisticians.”
How can natural language processing and data science help non-profits (charities) such as the White Ribbon Alliance analyse survey data and share it with the world? We have developed an interactive dashboard allowing members of the public to explore women’s healthcare requests around this world. We believe this is a first for transparency in the third sector. Click here to view the dashboard that Fast Data Science developed for the White Ribbon Alliance.
Is AI going to be a jobs killer? How many jobs will be lost to AI? What jobs will AI create?
Can we get rid of AI bias? Bias is one of the many imperfections of humanity that causes us to make mistakes and holds us back from growing and innovating. However, bias is not only a human reality, but is also a reality for artificial intelligence as well. AI bias is a well-documented phenomenon that is widespread among machine learning tools from a variety of sectors, and it is notoriously difficult to get rid of.
How do we apply ethics to artificial intelligence? Why do we now need AI ethics? What is AI ethics? The ever-expanding availability of big data and cloud computing, improved computing power, and recent developments in deep learning algorithms have paved the way for machine learning algorithms to transform nearly every industry.
How does Deep Learning work and are we really still in control? Deep Learning models are evolving, as are we Your mobile phone receives an alert. You take it from your pocket and look at the screen. Face recognition unlocks the phone, and you read a message your sister just sent. You laugh and then share it by selecting a group of friends who will also find it amusing. You add an instant voice message to the share and tell the phone to send it.
What is automated ML? Automated machine learning is software which in theory allows anybody to design, train, and deploy machine learning models to production environments without needing to write any code. It is often a drag-and-drop experience similar to PowerPoint.
Gender bias in credit scoring AI? In recent weeks a number of Apple Card users in the US have been reporting that they and their partners have been allocated vastly different credit limits on the branded credit card, despite having the same income and credit score (see BBC article). Steve Wozniak, a co-founder of Apple, tweeted that his credit limit on the card was ten times higher than his wife’s, despite the couple having the same credit limit on all their other cards.
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