The future is shaped by our present decisions and subsequent actions.
- We understand that we are valuable, but do we really know why?
- How are we intelligent?
- Are we intelligent?
- What does “progress” look like for you?
- What does a failure in “progress” look like to you?
- In these days of great challenge, where do you find inspiration to move forward, or do you feel your rudder is broken?
It is only the start of the COVID-19 pandemic, but the global community has already become more tied to online connections with the rest of the world than we could have ever imagined. As much as we saw risks of dependency and addiction to our devices rather face to face connections, we now just as readily see its potential and embrace it for our very survival. The urge to create online in order to connect has become more pressing than ever before. And one of these nights soon, I shall get off my device and go to the water’s edge away from urban light pollution and view the stars. With a decrease in air pollution, I look forward to a treat I haven’t enjoyed for more decades than I like to admit.
Artificial Intelligence is essential for compiling and collating more data than anyone could manually compile. AI is not a substitute for the human mind’s intuition, born from experience, to even begin to do intelligence analysis on the data. Intuition gives the person hints at what may be neglected among the data and check other angles to see if there is a connection. The AI is only as good as the input. It is only data. It is not intelligence analysis. If the right questions are not asked, the answers will never be found.
Even intelligent algorithms do not have a conscience. We need to be aware of what we are looking at in this field. If it was a question of whether to unplug the Internet, as some liked to speculate that the American military might, its connectivity’s essential nature in this pandemic precludes the likelihood of it ever happening. Although an intelligence analyst’s duty is to prepare to examine the least likely prognosis, it serves no good purpose to dwell on outlier speculation.
Machine learning is a subfield of artificial intelligence, categorized in three parts of supervised, unsupervised, and intelligently.
Associations between data and the labelled outcome/classification are derived from an algorithm with a set of prior, labelled examples. Differentiating between cat and dog uses pictures for contrast, a “supervised” interaction.
Uncategorized data does not infer on behalf of the computer. The computer deduces from the material itself the feline and canine differentiations. Its outcome would be interesting.
Heuristic learning is self or unassisted learning. This has been executed with chess games. It is the closest to “gut” ruling decisions, since “gut” and “intuition” are the sum of many pieces of information tugging into a direction of inquiry.
From using the silicon chemical, genetic algorithms, 3D microelectronic devices, and the artificial neural networks that are mostly indecipherable to human observers and human introspection for explainability. DARPA (Defense Advanced Research Projects Agency) of the U.S. Department of Defense) is keen to be in control of the AI for accountability and modifiability to correct malformed conclusions and eliminate incorrect facts (Husain, 46). We have a hard enough time with humans falling into that trap. The AI can do far more damage, and much more good.
On the 28th October 2016, Sichuan University extracted human immune cells, decoded and edited the genes (CRISPR-Cas9) knocking out the gene that keeps the body from attacking healthy cells. The genetically modified gene was introduced to attack lung cancer cells. “[C]lustered, regularly interspaced, short palindromic repeats” was based on the knowledge that “bacterial cells can indentify an invading virus and snip into its DNA.” (Husain, 65)
AI measures and tracks, models and predicts, gene edits, artificial narrow intelligence makes sense of invisible light, perfect sound memory and triangulation, perfect recall of imagery, prompts, satellite imagery and autonomous pocket drones that feed image to headset, and more.
But perhaps, it is artificial generalized intelligence (AGI) that concerns us most with its apparent intention and self-awareness massaging information into generalizations, cutting out the neglected outliers. The slippery slope is embedded within the parameters. It is such a concern, but we catapult on towards unmanned combat aerial vehicles (UCAVs) for scores of countries.
The tail seems to be walking the dog as AI is melded with our neural paathways to interpret signals. The AI replaces the connection between the brain and our limbs and muscles. Semantics means something, and I would prefer “bridges” the connection rather than “replaces,” but that is how delicate in meaning and intent that AI cannot fathom.
Husain has other chapters of interest. You can find The Sentient Machine on Scribd.
Amir Husain, The Sentient Machine: the coming age of artificial intelligence (Simon & Schuster, Inc., New York, 2017).
Ty Garibay, “AI And The Third Wave Of Silicon Processors” (Forbes Technology Council, 15 May 2018) https://www.forbes.com/sites/forbestechcouncil/2018/05/15/ai-and-the-third-wave-of-silicon-processors/#79d7682f6a47
“3D Self‐Assembled Microelectronic Devices: Concepts, Materials, Applications” (Wiley Online Library, 12 September 2019) https://onlinelibrary.wiley.com/doi/abs/10.1002/adma.201902994