“Could you please review all the previous pitch decks and substitute ‘crypto’ with ‘A.I.’?”
This particular line from a New Yorker cartoon by Benjamin Schwartz perfectly captures the emerging trend of AI washing in Silicon Valley.
AI washing may sound like just another marketing tactic, but it is a nuanced and intricate phenomenon. It is crucial for all readers of this article – whether technology leaders, marketers, product developers, users, or IT professionals – to recognize the exaggerations, skewed priorities, and outright falsehoods that permeate not only marketing and sales but also the narratives we consume based on industry assertions.
Unveiling the Facade of AI Washing
AI washing is a misleading marketing strategy that exaggerates the significance of artificial intelligence in the product or service being endorsed. The term draws inspiration from “greenwashing,” a concept introduced by environmentalist Jay Westerveld in 1986, where consumer goods are marketed as eco-friendly regardless of their environmental impact.
Products utilizing traditional algorithms are branded as “AI-powered,” capitalizing on the lack of a universally accepted definition of what constitutes AI. Startups develop applications that connect to a readily available generative AI API and market them as AI applications. Large-scale AI projects that are meant to showcase cutting-edge technology often rely on human intervention behind the scenes, as humans are indispensable for the successful operation of ambitious AI solutions.
Delving Deeper into the Human Element of AI
Retail behemoth Amazon introduced 44 high-tech stores under the Amazon Go and Amazon Fresh banners, leveraging its “Just Walk Out” suite of technologies (initiated in 2016). Amazon’s objective was to create stores where customers could enter, select items from shelves, and exit without encountering a cashier. Sensors, including cameras, fed data into AI systems to identify customers’ purchases and facilitate automatic billing – all without a traditional checkout process.
The system relied on advanced computer vision to monitor customer behavior and item selection. Shelf sensors measured the weight of items taken, corroborating the data captured by cameras. RFID tags provided additional product information. Sophisticated machine learning algorithms processed data from cameras and sensors to recognize products and link them to specific shoppers. Electronic gates controlled entry and exit, tracking customer movements.
These algorithms were trained on millions of AI-generated images and videos to identify products, human actions, and behaviors.
While Amazon has been forthcoming about the technical aspects of its Just Walk Out technologies for seven years, the company has been reticent about the approximately 1,000 human employees…
2024-07-20 09:15:02
Source from www.computerworld.com
