Welcome to Better Communication Results podcast 113.
In today’s show:
- How a new AI system, Mei, could help people understand each other better when they use technology to communicate,
- Taking charge of implementing artificial intelligence governance,
- Sprechen Sie AI? and
- DARPA invests $2bn in third wave AI
A new AI engine is about to launch publicly. Named ‘Mei’, it is an algorithm that reads your phone texts, reads the history of texts between you and your intended text recipients, and makes suggestions about tone and voice. It does this by building a personality profile of you and your text recipients.
It could, for example, suggest that the person you are texting with might be suffering from stress and need you to ‘check in’ with them. It could also, of course, be your recipient is very busy at the moment, hence the delay in responding.
This is all handled by Mei’s ‘relationship assistant’, which makes suggestions based on the age, gender, and personality traits of whoever a user is texting.
For example, if a contact’s messaging history implies that they are outgoing and spontaneous, Mei will suggest that you play things by ear when making plans.
For every positive in this technology, there is an equal negative. As with all artificial intelligence, the technology itself is neither good nor bad, harmful or benign. It is only the input and design biases and the outcome of the algorithm doing its thing that need monitoring.
The app also offers a range of features to take standard SMS messaging to the next level, such as self-deleting messages, end-to-end encryption, and the ability to un-send texts. The Holy Grail for angry, impulsive people, perhaps.
Currently, the engine only looks at your text history, but work is afoot to open it up to accessing other messaging systems, such as Facebook Messenger, WhatsApp, and so on. That would make it much more useful.
Taking charge of implementing artificial intelligence governance
The role of many senior leaders is changing, as organization strategies move to artificial intelligence governance.
Many organisations are realising that they have considerable stockpiles of data, but don’t know what to do with them all. Managers and leaders believe that there is value in the data, but are unsure how to realise that value. As healthdatamanagement.com said in a recent article, uppermost in leaders minds are issues such as the relevancy of the data, and which bits of data are more valuable (and thus should be extracted first).
To realize that value, Jean-François Gagné, chief executive officer at Element AI, said at a conference recently that organizations should create an AI governance framework that focuses on four key pillars: processes (including a focus on accuracy, bias and completeness); security (including a focus on adversarial robustness and adaptability); privacy (including focus on IP capture and impacted users); and transparency (including a focus on explainability and intent).
Sprechen Sie AI?
The folks over at website CIO Dive have given us an insight into why natural language processing can be so tricky in other languages. Google’s latest iteration of its ‘Translate’ app really is at the front of the line when it comes to translation technology.
As any student of language can tell you, copying and pasting a sentence from one language and hitting the ‘translate’ button is an exceedingly hit-and-miss affair. Rarely does the translation engine make a good, coherent, natural-sounding or natural-reading go of it. The technology is just not up to speed.
But when we humans communicate, even if we know we are chatting to an AI bot, we expect the conversation to be ‘human’. That expectation will be unmet, at least for a little while yet, but even more so when we are dealing with a foreign language.
US agency to invest $2bn to accelerate third wave of AI programmes
US Defence agency DARPA is investing $2bn in third wave AI programmes.
DARPA director Dr Steven Walker said: “With AI Next, we are making multiple research investments aimed at transforming computers from specialised tools to partners in problem-solving.
Today, says Walker, machines lack contextual reasoning capabilities, and their training must cover every eventuality, which is not only costly, but ultimately impossible.
Walker wants to explore how machines can acquire human-like communication and reasoning capabilities, with the ability to recognise new situations and environments and adapt to them.
As website army-technology.com says, the investment programme also intends to focus on reducing power, data and performance inefficiencies, and developing the next generation of AI algorithms and applications, such as explainability and common sense reasoning.
And that’s it for another episode of the Better Communication Results podcast. Subscribe to our podcast in iTunes, in your podcast app of choice, or over at Soundcloud. Or subscribe to our blog by filling in the form below these show notes.
Until next time, take care, take some communication risks, because you never know what is going to pay off, and communicate with passion.