Three times a day I take a drug called levodopa. I take it because my brain does not produce enough dopamine, without it my hands and feet shake and I have difficulty getting my body to do what I want it to do. These are symptoms of Parkinson's disease and mean that many of my dopamine producing neurons have died. But, thanks to levodopa, I can feed my brain synthetic dopamine. It is an incredible little drug that we discovered to be naturally produced in the broad bean plant, pictured here.

I'm currently working my way through the book Algorithms to Live By: The Computer Science of Human Decisions by Brian Christian & Tom Griffiths, which deconstructs many key life decisions into algorithms that can lead to optimal decision-making. As it cogently reviews many basic concepts using a wide range of life examples, I can see many ways in which machine learning techniques could sift through mountains of clinical data on cancer patients to help guide our management decisions in ways that elude the limitations of human brains. Oncologists work with patients to weigh decisions about whether a treatment with partial benefit (limited shrinkage of a cancer or even modest progression) is good enough to continue treatment and when a stronger choice is to change treatment approaches. When is is the expected benefit of more of the same, likely with a discount from diminishing returns, less than the anticipated or unknown benefits of the next alternative therapy? A well honed algorithm should be able to follow the growth kinetics of a cancer on scans and predict when it's time to change horses.

Science is slowly inching its way to discovering the secret to immortality. Human enhancement, as defined by transhumanists, is everything that "encompasses a range of approaches that may be used to improve aspects of human function." Human enhancement is currently being researched in institutions such as Stanford University, which has recently devised a mathematical algorithm, called ReFIT, that can decipher neurological signals in the brain that convey movement, speed and accuracy. While the public justification of the study is to improve "prosthetic system performance and robustness in paralyzed people," its implications are far-reaching. The FDA has approved ReFIT for human clinical trials as researchers work to create neuroprosthetics for mind–controlled robotic limbs.