The line between human and machine authorship is blurring, particularly as it's become increasingly difficult to tell whether something was written by a person or AI. Now, in what may seem like a tipping point, the digital marketing firm Graphite recently published a study showing that more than 50% of articles on the web are being generated by artificial intelligence. As a scholar who explores how AI is built, how people are using it in their everyday lives, and how it's affecting culture, I've thought a lot about what this technology can do and where it falls short. If you're more likely to read something written by AI than by a human on the internet, is it only a matter of time before human writing becomes obsolete? Or is this simply another technological development that humans will adapt to?

Instructional texts for specific target groups should ideally take into account the prior knowledge and needs of the readers in order to guide them efficiently to their desired goals. However, targeting specific groups also carries the risk of reflecting disparate social norms and subtle stereotypes. In this paper, we investigate the extent to which how-to guides from one particular platform, wikiHow, differ in practice depending on the intended audience. We conduct two case studies in which we examine qualitative features of texts written for specific audiences. In a generalization study, we investigate which differences can also be systematically demonstrated using computational methods. The results of our studies show that guides from wikiHow, like other text genres, are subject to subtle biases. We aim to raise awareness of these inequalities as a first step to addressing them in future work.

Incorporating biometric technology into your access control system can solve some of these challenges, and it's likely that you've done your research and product comparison on the various biometric solutions that exist in the market. There are a few options to consider, including fingerprint or iris scanning, voice detection, and – most prominently – face recognition. In this eBook by Oosto we will dive deep into the 4-step process of implementing visually intelligent access control and how visual intelligence not only solves major challenges, but also offers a number of additional benefits. Please fill out the following brief form in order to access and download this white paper.

Do you have any insights into a career in brain-based AI? What do I need to study if I'm interested in developing Numenta's technology? Where can I learn the necessary skills? These are some of the questions we receive quite frequently from students interested in pursuing a career in brain-based AI. Not too long ago, the AI/ML conversation was largely centered around making machines that can outperform humans at specific tasks by identify patterns in data.

The field of neuromarketing is still in its infancy, but it's growing fast as the ability to track and monitor consumer brain activity becomes more widespread. While American companies have been pioneers in this field, many European businesses are just now starting to hop on board with neuromarketing research techniques. This article will serve as a quick guide for companies looking to implement neuromarketing principles and tactics into their marketing research endeavors. Neuromarketing is the study of human brain activity that is triggered by exposure to stimuli in marketing research. This could include exposing participants to products, websites, advertisements, or packaging in order to determine how each stimulus elicits a physical or emotional response.