We are excited to share our December issue about artificial intelligence (AI) and machine learning with you. Although this issue is a shorter one, we are excited for you to explore these topics with us, topics that are no longer solely constructs of science fiction, but important aspects of modern daily life.
Despite the promise of using AI for humanity’s benefit, the idea of a faster, stronger, and more intellectually powerful entity sharing our planet often inspires science fiction stories of utter disaster. Skynet from The Terminator or HAL from 2001: A Space Odyssey evoke an image of human inferiority bound to be overcome and replaced by a superior artificial intelligence. In this issue, we aim to shed light on some of these concepts and misconceptions, and to address the state of the real challenges faced by scientists developing machine learning and artificial intelligence tools for human benefit.
Artificial Intelligence encompasses devices and programs that are able to perceive their environments and act upon their observations to optimize their chance of attaining their goals. Machine learning is a subgroup of AI and is the science of designing and using computer algorithms to recognize patterns in large datasets. This process is not accomplished by machines alone, but is enabled and influenced by the individuals providing data to train the programs to perform their tasks. Put differently, the patterns recognized by an AI are dependent on the quality of information used to teach the algorithm what to look for. In this way, machine learning algorithms are nimble performers of simple tasks rather than sentient evaluators of information.
Artificial intelligence products exist today and are improving rapidly, making these machines better and faster at tasks but not necessarily more self-aware. To date, these algorithms remain as resources for human productivity and are not an immediate threat as a competing form of intelligence. The reality is that machine learning methods are powerful tools with potential yet to be fully realized. We hope that this issue will provide some insight into the current state and future of artificial intelligence, and that it will inspire our readers to think critically about their own opinions and biases regarding artificial intelligence and machine learning.
Nisar Farhat, Alex Sercel, and Stephanie DeMarco