Data science and machine learning professionals now know how to look for answers in data: that's probably the central pillar of your work. Things get murkier when we look at some of the thornier questions surrounding our data, from its built-in biases to the ways it can be leveraged for questionable purposes.
As we enter the home stretch of the year, we invite our readers to explore some of these broad themes that have sparked crucial debates in recent years and will surely continue to shape the field in 2024 and beyond.
Our highlights this week delve into a wide range of topics, from the nature of data-driven insight to its application in specific fields such as healthcare; We hope they inspire further reflection and attract new participants to these essential conversations.
- What role should ai play in healthcare?
The biases we've covered so far can wreak havoc on models, companies, and results. As Stephanie Kirmer However, these tensions are even more acute in fields such as healthcare, where life-or-death situations are common and “the risks of failure are very catastrophic.” - A Requiem for the Transformer?
In a rapidly changing field, it's tempting to think that the concept of a 6-year-old is essential and timeless. Transformers have been around since 2017 and have played a major role in the widespread adoption of ai tools; as Salvatore Raieli However, he points out that they very likely have a useful life and it might be a good time to ask what comes next.
