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AI Musings: Using Image Classification Creatively and the Coming Collision in City Centers

Within this supercycle of digital innovation, we are experiencing globally; AI is revolutionizing business both in predictable and unpredictable ways. With an expectation of more than $20 trillion added to the global economy by 2030, the impact of AI on business is real. While most of the patents and citations are still coming from the US, China is rapidly gaining citations. The Standford AI Index has some compelling data in its 2019 index, but not sure when they will publish the 2020 index. The current index is probably worth a look if we like numbers.

Creative Data Sets

Being immersed in AI now and well into the future, and that the current UC Berkeley School of Information AI Strategies course draws to a conclusion, we wanted to leave our readership with some thoughts on ways diversity of a single classification dataset, when used creatively, can develop abstract, unique and ingestible modeling. Further, as our interaction with devices gets more interactive, our devices will get smarter and more creative. The more we interact explicitly with messaging from Zoom or What’s APP (how was the quality of your video content), the smarter the apps will become, which means more upskilling for you in the future.

Let us start with data augmentation, which is different from augmented reality. A personal and realistic approach or example would be a set of pictures classified in computer vision as an Armenian Orthodox Church. Just by turning the picture upside down, we would realize an entirely new and abstract data set. A picture of an Armenian Orthodox Church steeple, right side up, if turned upside down, could also potentially be classified as a standard female sex symbol. The output generated from this abstract data set might be a bevy of sexy female Armenian priests, but you get my drift, assuming specific model parameters were lifted. ComputerVision with classified images is decisive for the creative mind and very different from Augmented Reality; we can identify with other unique data sets just by changing the picture’s angle.

Equally important, the arts expand traditional notions of what it means to be human, which are often taken for granted in technological innovation. It is frequently through the arts that we see more expansive, richer understandings of humanity, ones that challenge our enshrined notions of how bodies can or should move, how art is perceived by different humans, look, communicate, or gain accessibility.

“In fact, we are seeing more nuanced opportunities for partnerships between AI and the arts to advance the ‘humane’ by better representing the fullness of humanity,” - Michele Elam

The Collision of Humans and AI in City Centers

AI is eating software. We hear about the global footprint in investments in Autonomous Vehicles, Drugs, Cancer and Therapy, Video Content, Facial Recognition, Fraud Detection, and Finance. However, we do not hear too much about where AI plays an increasingly important role in decision making at the intersection between humans and robots.

We know that city centers will have autonomous vehicles, and there will be no human-driven transit vehicles or cars within these city centers. Autonomous Vehicles will be driven at a maximum speed limit to ensure safety within this 1-2 mile radius of city centers. What is also apparent is that these systems will not be optimal in conjunction with human drivers. We cannot allow a human driver to interact with an autonomous vehicle, especially for pedestrians and occupants’ safety in these vehicles optimally. Within these city limits, decisions made by self-driving cars, driven at a maximum speed-limit, will be far different from decisions made by humans. For a human driver to successfully interact with self-driving cars, we have to upskill and future-proof our interactions with these self-driving vehicles and upskill our interaction with all of our devices. Full AI trust cannot be associated with a human because of bias. For safety and efficiency from a transport perspective, decisions made by machines will have one set of biases (albeit built by a human), and humans driving will have another set of bias.) If, for example, you have just one human driving within these city limits, you would already have two data sets.

Finally, the impact this advance will have on individuals is that people will start to get accustomed to interacting with machines as if they were humans. There may even be cases where someone may be surprised or even shocked that the other person at the end of the phone line, with whom a long term dialog has been taking place, is revealed to be a machine and not a human. The more and more AIs become pervasive, the less and less we will recognize them as being something out of the ordinary.

By Fred Tabsharani, Founder and CEO at Loxz Digital Group

Fred Tabsharani is Founder and CEO of Loxz Digital Group, A Machine Learning Collective with an 18 member team. He has spent the last 15 years as a globally recognized digital growth leader. He holds an MBA from John F. Kennedy University and has added five AI/ML certifications, two from the UC Berkeley (SOI) Google, and two from IBM. Fred is a 10 year veteran of M3AAWG and an Armenian General Benevolent Union (AGBU) Olympic Basketball Champion.

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