AI–driven products will involve new workflow, different sets of moving parts, and new type of relational logic. One way to untangle this problem is to find a common, ubiquitous element in today’s digital design, and consider how likely is it to change.
Source: Why Should Designers Care About AI? | Nitzan Hermon | Pulse | LinkedIn
MVC, in its current format, can’t handle new technologies such as machine learning and artificial intelligence. These new environments will require new and far more complex architectures (MVC shortcomings are already apparent). For design this is likely to be as much of a defining experience as the shift from print to digital. It is fascinating to think about the fact that we’re reaching a point where we will be designing systems, quite literally, instead of views.
Source: Design for AI: Thinking Beyond MVC
The machines will be able to enslave you in your native language.
Source: Google is using neural networks to improve Translate
As our technological and institutional creations have become more complex, our relationship to them has changed. We now relate to them as we once related to nature. Instead of being masters of our creations, we have learned to bargain with them, cajoling and guiding them in the general direction of our goals. We have built our own jungle, and it has a life of its own.
Source: The Enlightenment is Dead, Long Live the Entanglement
At first, the Go champion thought the move was rather odd. Then he saw it was wonderful.
Source: The Sadness and Beauty of Watching Google’s AI Play Go
But building voice technology on a 26-year-old corpus inevitably lays a foundation for misunderstanding. English is professional currency in the linguistic marketplace, but numerous speakers learn it as a second, third, or fourth language. Gavaldà likens the process to drug trials. “It may have been tried in a hundred patients, [but] for a narrow demographic,” he tells me. “You try to extrapolate that to the general population, the dosage may be incorrect.”
Seems like a huge problem of bias if voice systems are trained on such an old and narrow set of data.
Source: Voice Is the Next Big Platform, Unless You Have an Accent
Challenges with second wave: Statistically impressive, but individually unreliable
Third wave: Contextual adaptation: Systems construct contextual explanatory models for classes of real world phenomena
Source: DARPA Perspective on AI
This is the Executive Summary of VoiceLabs’ 36-page 2017 Voice Report, highlighting key analysis and predictions.
Source: 2017 Voice Report | VoiceLabs
But what if bots conversed with us in a new way that is uniquely bot-like? At the moment, we anthropomorphize bots because we’ve never really had any non-human entities occupying conversational space with us. Could we create a new set of expectations and aesthetics that might ameliorate these social challenges and create new conversational possibilities? How might a machine express itself in ways that set up new kinds of expectations for our interactions with it?
Source: Mechanomorphs and the politeness of machines | nytlabs ← Research, thoughts, and process from The New York Times R&D Lab