Tagged: ML

Nokia on Design Thinking, AI and starting with what users need


“Any organization that wants to deliver targeted, personalized services and experiences needs to understand its customers inside and out: their wants, wishes, behaviors and attitudes.”

“These days, the data to develop that understanding is abundantly available. The challenge is to extract meaningful customer insights from it and convert those insights into actions.”

“By combining the principles of Design Thinking with the power of Artificial Intelligence (AI), CIOs have the tools to solve that problem and deliver powerful business results for their organizations.”



Design Thinking, AI and starting with what users need” was just released this past October 15. The full article is available on CIODIVE, which I am proud to co-sign with Santeri Jussila, Head of Analytics Product Line at Nokia Software. Also thanks to Nokia’s own Patty Wong, Malla Poikela, Araceli del Rio and Marcelo Fabri. What follows is some additional color commentary and additional insights.


Reviewed on Sunday, October 20.

Design visions in the making.

I truly believe that these are exciting times. Often enough we recall and discuss visions conceived decades ago. We marvel about our predecessors’ foresight. Then we wonder about what’s actually truly new these days as we reach the magical 2020 time horizon: are we still innovating or just rehashing old concepts? Besides, what is the meaning of “real” and “true” in what the Oxford Dictionary defines as the post-truth era?

The fact is that a reality check unveils a thriving ecosystem economy where a number of the bits-&-pieces that any of us need to innovate with are coming together. Better yet, this is also happening at accelerated speeds and cost effective levels. In turn, Design Thinking is fostering new foresight around the possibilities ahead… basically, new visions in the making.


There is more to 5G.

As shared in the CIODIVE article, 5G has become a galvanizing technology. 5G goes well beyond radio optimization outpacing what 4G and earlier wireless systems had to offer. To be more specific: we are intersecting: lightspeed networking, scalable virtualizaiton, dynamic software defined instruments and systems, actionable analytics, agile automation… and new levels of programmability, all equipped with unprecedented intelligence.

Speaking of intelligence, the best that cybernetics has to offer comes in the form of context-aware and always-learning systems optmizing for exploration, decisioning and control. Their growth and high performance are driven by adaptive closed feedback-loop workflows, which entail both, human and machine smarts.


Fast evolving HMS, Human Machine Systems.

We all know and, nonetheless, history keeps reminding us that technical prowess alone does not suffice. At Nokia’s Venture Studio we are working on outcome-oriented HMS, Human-Machine-Systems.

This is why we purposely focus on usefulness, utillity, usability and affectivity values. In our line of work, Human Centered Design (HCD) and Human Factors Engineering (HFE) make a compelling difference.



Our thinking behind the design of Human-Machine-Systems is that they should be conceived and stress-tested for effectiveness (e.g. getting the job done, delivering meaningful results) and efficiency (e.g. optimizing resource utilization levels, maximizing value) as well as getting only smarter iteration after iteration, cycle after cycle.


Nokia Venture Studio.

Delivering High Performance Environments (HPE) and Quality Experiences by Design (QXbD) inform our Studio’s meta-methodology, lead to fluid practices and, equally important, signal a distinctive creative workstyle.



Digitizing the Digitalization Era.

It does not hurt to state the obvious: digitalization is now pervasive. Following that train of thought, digitalization also means both on-demand lightspeed consumption and instant mass personalization.

It means democratizing tech so that the digital divide becomes a thing of the past and no-one is left behind. It means self-service empowerment and curated expert services as needed.

It means scaling at speed and greater scope than ever before. It means clever centralization to leverage shared resource pools and operational efficiencies. And it means even smarter and highly dynamic decentralization as we get closer to the end user and effectively optimize on the basis of the experience economy. This is a hybrid world in permanent motion with any “thing” (and anything) is provided as a service, anywhere, anytime. Watch for ripple effects.


Digital Services by Design.

From a Service Design standpoint, the backstage’s operational experience entails painstaking work on: redefining success and outomes, job re-design, process re-engineering, and setting the state-of-the-art. Addressing these happens to be critical success factors.

I will be more specific. DTV, Design to Value, now means that we need to design and gear up for signature experiences. These register delight, rather than just conforming to yesteryear’s cookie cutter market segmentation and just aiming to “satisfy.” We are going past “segmentation” and “personas” to better act on “persona-lization” – segment-of-one in other words.

Digitalization’s paradoxes are here and in full force: (1) we are purposely shifting the “new normal” by creating opportunities to pleasantly “surprise and differentiate” rather that just normalize, standarize and penalize deviation or outliers; (2) the more we talk about extreme automation and zero touch systems, the more (not the less) humans (and a more diverse population) gets to interact with sophisticated systems otherwise formerly restricted to domain experts and obscure fields.



Designing for “digital transparency” brings you user friendly self-service, recsys (recommender systems) affective computing and xAI, Explainable Artificial Intelligence, just to name a few examples. We can now design for the senses and do that by engaging in natural language and with immersive and interative infographic visualization.

As Arthur C. Clark’s third law stated: “any sufficiently advanced technology is indistiguishable from magic.” Also bear in mind that his second law was: “the only way of discovering the limits of the possible is to venture into the impossible.”



It’s about culture…

At Nokia’s Venture Studio, our work and craftsmanship is the product of a thriving culture, one that we are also consciously influencing and shaping (think Escher’s Drawing Hands) to adequately foster human possibilities.

IEEE CQR 2018 – AI CoC Session

 


IEEE CQR-ETR 2018: “Discuss and identify the RAS (Reliability, Availability and Serviceability) challenges, requirements and methodologies in the emerging technology areas like the Cloud Computing, Wireless/Mobility (with focus on 5G technologies), NFV (Network Functions Virtualization), SDN (Software Defined Networking), or similar large-scale distributed and virtualization systems.”

“Discuss the RAS requirements and technologies for mission-critical industries (e.g., airborne systems, railway communication systems, the banking and financial communication systems, etc.), with the goal to promote the interindustry
sharing of related ideas and experiences. Identify potential directions for resolving identified issues and propose possible solution.”


IEEE CQR ETR 2018 1


Session Title: A Programmatic Approach for an Artificial Intelligence Code of Conduct.

Today’s DX, Digital Transformation, programs are all the rage, but it takes a fair amount of double clicking and inquisitive questioning to separate facts from vaporware. DX typically involves a wide variety of game changing initiatives intersecting analytics, automation, programmability, software-defined systems, end-to-end integration, service-level composition and controls… all coming together to optimize for Quality as a differentiated and value-based Human Experience. Therefore, Customer Delight metrics (rather than outmoded customer satisfaction ones) are set to redefine the “Q” in CQR, Communications Quality & Reliability in 5G.

While the Telecoms industry rallies toward a zero-touch automation paradigms, which some happen to position as a Human-“OFF”-the-Loop panacea, this session will expose the need for considering, and possibly pivoting, to the kind of Operational Excellence that can only be delivered by adaptive HMS, Human-Machine-Systems instead.

Note the rise of Dataviz (Data and Science Visualization,) ML’s (Machine Learning’s) Collaborative Filtering, AI’s (Artificial Intelligence’s) RecSys (Recommender Systems) and a renewed take on Cybernetics are driving innovation in HILT and HOTL (Human-“IN”-The-Loop and Human-“ON”-the-Loop, Computing,) as well as delivering effective mass-personalization with Affective Computing powered by Human Dynamics’ analytics.

Telecoms’ pioneered HFE, Human Factors Engineering: a holistic systems engineering discipline addressing people (culture, workstyle, skills,) processes (procedures, methods, practices,) and technologies (crafts, tools, systems) so that we can best humanize technology and make a compelling difference across the value chain at all levels. We are now embarked on a new journey.

The sought after outcome of any Digital Service Provider, DSP, is to be instrumental to our Citizens’ Quality Experiences with new service experimentation, transactions and growth models. This takes agility and dynamic system-wide (horizontal and vertical) behaviors, which prompt effortless operability at unprecedented speed, scale and scope. Our work permeates design, development, delivery and serviceability, and continuous intertwined lifecycles instead of lock-step waterfalls.

In this context, AI, Artificial Intelligence, enables us, humans, to envision and implement capabilities beyond the reach of legacy systems’ last gasps. By the same token, practices that might have appeared to serve us well in the past, are exposing their limitations when becoming latency-prone barriers. A successful path forward takes augmented Human-Machine Intelligence. A programmatic approach for an AI’s Code of Conduct would enable us to best model AI’s behavior, design better human-network interactions and collaborate on standardization.