In the coming months, NYC Mayor Bill de Blasio will announce a new task force on “Automated Decision Systems” — the first of its kind in…
While these systems are already influencing important decisions, there is still no clear framework in the US to ensure that they are monitored and held accountable.¹ Indeed, even many simple systems operate as “black boxes,” as they are outside the scope of meaningful scrutiny and accountability. This is worrying. If governments continue on this path, they and the public they serve will increasingly lose touch with how decisions have been made, thus rendering them unable to know or respond to bias, errors, or other problems. The urgency of this concern is why AI Now has called for an end to the use of black box systems in core public agencies. Black boxes must not prevent agencies from fulfilling their responsibility to protect basic democratic values, such as fairness and due process, and to guard against threats like illegal discrimination or deprivation of rights.
This is a rather difficult “entity” to design an identity for — it’s not an identity for a restaurant or a company selling shoes or even a telco — as there are few points of reference or comparison for anyone involved (from client, to designer, to audience). This is similar to IBM Watson’s identity in that it has to give voice and personality to an ambiguous thinking brain making decisions while trying to make it marketable at time where there aren’t that many mass-market artificial intelligence platforms to compare against.
Our problem isn’t that Artificial Intelligence is getting better at being human, it’s that human beings are getting worse at it.
Using Google Clips to understand how a human-centered design process elevates artificial intelligence
As was the case with the mobile revolution, and the web before that, machine learning will cause us to rethink, restructure, and reconsider what’s possible in virtually every experience we build. In the Google UX community, we’ve started an effort called “human-centered machine learning” to help focus and guide that conversation. Using this lens, we look across products to see how machine learning (ML) can stay grounded in human needs while solving for them—in ways that are uniquely possible through ML. Our team at Google works across the company to bring UXers up to speed on core ML concepts, understand how to best integrate ML into the UX utility belt, and ensure we’re building ML and AI in inclusive ways.
Source: The UX of AI
Designed by Argodesign and CognitiveScale, Cortex offers a glimpse at the future of accessible AI design tools.
The result is a simple honeycomb-like switchboard where you drag and drop bubble-like skills; blue and green lines show the flow of data as it moves into and out of each skill. Conceptually, it feels like Garageband, but for AI.
New Institute-wide initiative will advance human and machine intelligence research.
MIT is poised to lead this work through two linked entities within MIT IQ. One of them, “The Core,” will advance the science and engineering of both human and machine intelligence. A key output of this work will be machine-learning algorithms. At the same time, MIT IQ seeks to advance our understanding of human intelligence by using insights from computer science.
The second entity, “The Bridge” will be dedicated to the application of MIT discoveries in natural and artificial intelligence to all disciplines, and it will host state-of-the-art tools from industry and research labs worldwide
Symbolic language can help us grasp the nature and power of what is coming.
The following metaphors are gleaned or created from reading Superintelligence and the literature around ASI. These metaphors are speculative, heavily implied by Bostrom’s own speculations. Some metaphors are galactic; some are more local, intimate. All are, hopefully, not anthropomorphic (naive). They are just initial gestures at a very loose glossary that could grow over time.
A hurricane is a most sublime metaphor, perfectly attuned for how potentially destructive a true ASI could be. The hurricane is terrifying meditation…
7 steps to stay focused on the user when designing with ML
If you could choose one photo to represent "machine learning", what would it be?
I'm sick of pulsing brains of 1s and 0s or people standing around a chalk board.
— Hilary Mason (@hmason) November 28, 2017
The best way to maximize the impact of any technology is to make it as accessible as possible. Only then will AI begin to creep into ordinary offices and workplaces. DataRobot is already being used in some of those settings.