Relaxing with family one Sunday, my dad said, “The TV knows what I like without me telling it; it is smart.” He wanted an explanation of the interplay between what appeared on his mobile phone and TV. “It knows a lot about me,” he stated with both curiosity and concern.
The “it” is best described as embedded AI, which is how technology firms create intelligent platforms that enable smart interactions with and integration into our everyday life experiences. This idea of embedded AI could clearly be seen at Apple’s Worldwide Developers Conference last month. Some would contend that Apple is late to the AI ecosystem as we have come to know it, with ChatGPT, Google AI, Microsoft Azure, Copilot, Tensor Flow and many others already on the scene. Rather, it seems to be fashionably late, upstaging competitors with news that its AI product, which it calls Apple Intelligence, will span its critical core devices: iPhones, Macbooks and iPads.
Apple Intelligence demonstrates the embedded nature of integrated product and services, coexisting to produce a platform intelligent experience for billions of users while incorporating ChatGPT. And it’s likely to change the way we use our devices and AI.
Data from Statista shows that in the second quarter of its 2024 fiscal year and for iPhones alone, Apple generated close to $46 billion in revenue. As of June 2024, Apple continues to lead in the mobile vendor market share, according to the same source. While these data show an integration among products, the associated embedded nature of Apple Intelligence is seamless along service offerings—which, in part, answers Dad’s question.
Interestingly, Meta is also showing integration of AI products and services using an embedded AI approach. Using Llama 3, Meta AI is said to be the most intelligent AI assistant. It’s integrated in Instagram, WhatsApp and other company products. Having acquired Instagram in 2012, Meta continues to add more functionality to the IG platform, including photo and video sharing, Reels, Live Rooms and Collab.
By 2025, forecasts predict there will be 1.44 billion monthly active users of the social media platform, which would account for 31.2% of global internet users. If we look at IG’s market penetration along and with the incorporation of Meta AI, users can seamlessly get real-time information via a Meta AI “personal assistant” to generate and manage daily tasks. In the case of my dad, AI-generated reels in IG can potentially enable personalized-TV based on user-desired and -inspired content.
With the generative nature of embedded AI, intelligence and personalized approaches, there is a new blueprint. AI appears to remove the human “thinking” that comes with even the most mundane tasks that we all experience daily. Rather, it is selecting a TV show to watch, creating a calendar event or writing an email. Embedded AI is integrated into widespread devices and applications to offer users ease-of-use and information sharing across products and services. While this embedded approach can be convenient and offer increased productivity, it can also go too far, stripping us of our ability to think, create and reflex for ourselves.
As we approach AI innovations, this embedded nature will transform daily life in three fundamental ways:
- Intelligence will take on new meanings and experiences for tech users. The era of device, platform and data has collided, and they are now almost inseparable. For example, personal search on a single mobile device gives results across each device that is linked to the user. In dad’s case, TV results on the mobile phone are now linked to and embedded on his tablet and laptop.
- Platform intelligence associated with AI innovation will challenge our ways of thinking through even the simplest of tasks. Yet, human assessment and creativity are needed in the design, creation and inception of AI products and services. Consider the diversity of languages, cultures and backgrounds that intelligent products and services should take into account.
- AI will continue to be shaped by how we live, work, play and interact. With this, data privacy and protection are concerning issues. Technology continues to outpace legislation, and the need to data literacy (at even a baseline level) is critical. These raise issues of responsible AI, AI bias and ethical AI. In each case, transparency, accountability, equity, fairness and governance become central themes as embedded AI is and will become more intelligent.
My dad’s statement, “it knows a lot about me,” offers a glimpse into why platform intelligence must be transparent and paired with human inquiry, allowing room for all of us to think for ourselves.
