There has been a dramatic increase in media interest in Artificial Intelligence (AI), in particular with regards to the promises and potential pitfalls of ongoing research, development, and deployments. Recent news of success and failures are often presented as supporting evidence for hope or hype of the journalist’s bias. E.g., the existential opportunities and threats of extreme goals of AI (expressed regarding Superintelligence/AGI and Socio-Economic impacts) are prominent in this media “frenzy.”
We need to learn some lessons about our public presentations in this domain, to avoid this display of excessive exuberance. In that respect, it is useful to get perspective via a critical review of this media coverage. And, from that, to find lessons on being perhaps more modest on project naming/claiming in the AI space. Perhaps we need to be more precise and offer realistic short term goals of achieving simply really useful machine learning (RUML<sup>SM</sup>), with specific smart components.
An example of this a calvIO Inc project in Machine Learning in the Industrial Robotics space, namely the RUML<sup>SM<.sup> project. It is a novel AI/Machine Learning system (Patent Pending) that is proposed to resolve some of the known issues in bottom-up Deep Learning by Neural Networks, recognized by DARPA as the “Third Wave of AI.”
The above was the basis of a paper presented at 4th International Conference on Artificial Intelligence and Applications, organized by the Academy & Industry Research Collaboration Center (AIRCC) , presented on the 25th March 2017 in Geneva, Switzerland.
The full paper can be accessed here: http://airccj.org/CSCP/vol7/csit76607.pdf