Communicating results from scientific investigations is an important facet of the biomedical research community. The dissemination of data allows others to build upon what has already been accomplished. Nevertheless, the current style of oral presentations undercuts the assessment of the original data. Investigators routinely put more data into a single slide than can be described in an intelligent way in the time allotted. The features of the data are not pointed out, the source of the data is ignored, and how the data inform the interpretation is neglected. There is often so much data on the slide that it is impossible for those in the audience to find what data are being referred to and to discern whether the data are believable and compelling. The consequence of flashing so much data on a slide and in a seminar is to devalue the data. Instead of focusing on individual datapoints to make an argument, talks are full of cartoons and diagrams that presuppose the data and the reasoning. The presentation of conclusions from studies involving artificial intelligence are particularly difficult to present orally since the algorithms used to reach conclusions are not considered and usually not even mentioned. These attributes of oral presentations are symptoms demonstrating a disregard for the original data.