Tagged: Recommender Systems

The rise of Digital Decision Support Systems and the Integrated Workspace


BI Summit Chicago

ABSTRACT

Digital Transformation drives today’s Workforce Automation and Business Intelligence (BI) initiatives where nimbler agile teams undertake tasks and jobs of unprecedented scale, scope and speed.

Digitalization also involves “Self-Service” business models which are based on the direct involvement of end-users and a frictionless customer journey, all relaying on seemingly instantaneous and automated mass-personalization.

Given that digitalization has become pervasive and that ‘making tech human’ has become a critical success factor, the new field of Genuine Intelligence (GI,) addresses holistic Human-Machine-Systems (HMS) leveraging collaborative environments comprised of networked insights, tools and processes. GI’s signature deliverable is Digital Decision Support Systems involving Integrated Workspaces.


ADDITIONAL INSIGHTS

This construct adheres to LeanOps and Quality by Design (QbD) principles for emerging technologies and, therefore, optimizes for (a) quality outcomes as gauged by consumer and operational experiences performed under (b) highly efficient operations and (c) advantageous resource utilization and effort levels.

Both value generation and productivity gains are constantly audited and iteratively improved throughout event lifecycles and over the lifespan of the system.


Nokia Keynote


BIO

Jose de Francisco is a Senior Design Director at Nokia Software Group. His 20+ year experience encompasses multi-disciplinary leadership responsibilities in strategy, product & portfolio management, research & development, marketing, partnerships and project & program management. Jose is a Distinguished Member of Technical Staff (DMTS) and has worked with Bell Labs on next generation platforms. He is a Member of the Advisory Board at MIT’s Institute for Data Systems and Society (IDSS) and is the recipient of an MBA in International Marketing and Finance (MBA/IMF) from Chicago’s DePaul University as a Honeywell Europe Be Brilliant Scholar. Jose also holds a postgraduate degree in Human Factors Engineering from BarcelonaTech (UPC) and can be followed on innovarista.org.

 

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.