How AI ethics falls short - preserving jobs is not enough
Diginomica.com
December 07, 2021
AI ethics has been a hot topic for about five years, but are we getting to the fundamental issues? Here's why well-intentioned ideas for preventing AI job loss come up short.
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Tags: Analytics, AI, Predictive Analytics
Technology for Operational Decision Making
Hired Brains Research
August 29, 2021
Success in business relies on making the right decisions
at every level. Organizations and executives focus on
high-impact, strategic decisions. Operational decision
making is often neglected because the individual
front-line decisions seem to lack impact. This is
a mistake because these little decisions add up. A
company’s brand identity is defined by thousands
of these little decisions
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Tags: Analytics, Predictive Analytics, Change Management, Business Strategy
Market Report: Technology for Operational Decision Making
Smartenoughsystems.com
March 18, 2021
Analyst Market report on technologies and methodologies for implementing decision management
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Tags: Analytics, AI, Predictive Analytics
Ethical Use of Artificial Intelligence for Actuaries
Society of Actuaries
February 25, 2021
In-depth report of the state of AI Ethics and recommendations for the Society of Actuaries to up date the Code of Practice to include AI.
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Tags: AI, Predictive Analytics, Change Management
Natural Language Processing Augmented Analytics
Vertica
February 03, 2021
What stops analytics from becoming part of everyone’s daily routine? It isn’t a slacking data engineering team, or an imperfect data architecture, it’s the interface. If I need to know something for my job, instead of learning complex SQL queries, or interpreting a bunch of graphs, why can’t I just ask?
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Tags: Analytics, AI, Predictive Analytics
Data in Mind, Data in Hand: Frictionless Provisioning for Data Science and ML/AI with DataOps
Hired Brains Research
October 07, 2019
Data in mind, data in hand is a concept that shrinks the effort and latency from conceiving of a model and having the data to run it.
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Tags: Agile, Analytics, Big Data
Practical Examples of the Impact of AI in Data Management
Hired Brains Research
August 07, 2019
Data catalogs emerged as the must-have technology for dealing with vast collections of data files. But
a data catalog alone does not solve the problems facing organizations of providing a simple discovery
tool. A static catalog lacking an in-depth understanding of the variety of data formats only addresses
a fraction of the problem. The application of AI to provide recommendations of mappings of data
sources, and exposed through Natural Language Query, search and exploration in your own words with
continuous update, makes this possible.
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Tags: Analytics, Big Data, Predictive Analytics
The cloud data migration challenge continues - why data governance is job one
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May 03, 2022
Cloud data migrations can bring significant operational benefits - not to mention opening up AI/ML use cases. That doesn't mean these migrations are easy. Getting migrations right starts with data governance.
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Tags: Analytics, AI, Big Data
Solving the data wrangling conundrum - can machine learning transform data management?
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April 26, 2022
Do data scientists really spend 80% of their time wrangling data? Last time around, we examined this notion. But when it comes to data management, how can machine learning change data platforms for the better?
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Tags: Analytics, AI, Big Data
Data science myths and realities - do data scientists really spend 80% of their time wrangling data?
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April 20, 2022
Do data scientists really squander the bulk of their time cleaning data sets? Not necessarily - but for robust machine learning models, we do need better data management platforms.
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Tags: Analytics, AI
From autonomous cars to autonomous weapons, the AI ethics issues can't be ignored
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April 05, 2022
Autonomous technology is racing towards us. But whether its autonomous cars or autonomous weapons, there are serious questions. This is where AI ethics comes to a head.
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Tags: Analytics, AI, Big Data
Can AI help to address the looming global food crisis?
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March 29, 2022
The global food supply is under duress, with Russia's invasion of the Ukraine applying even more pressure. With world populations mounting, can AI make a difference in farming and agricultural yields?
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Tags: Analytics, AI, Big Data
Quantum computing scenarios - the case for hybrid computing models
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March 22, 2022
Supposedly, quantum computing ushers in an age of revolutionary possibilities - thanks to quantum's unprecedented computing power. But the most compelling scenarios are actually a "hybrid" mix of quantum and classical computing.
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Tags: Analytics, AI, Big Data
Here's looking at you, kid - the problematic adoption of facial recognition systems
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March 15, 2022
Facial recognition systems are one of the most controversial areas of real world AI. But despite the ethical qualms, facial recognition is now in use across multiple industries. Can regulation catch up?
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Tags: Analytics, AI, Big Data
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March 08, 2022
DARPA has an aura of mystery around it, and is most often linked to the US Department of Defense. But DARPA's innovations frequently find their way into the enterprise - including important AI developments.
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Tags: Analytics, AI, Big Data
Towards a semantics of data in a digital world - why is effective data collaboration so elusive?
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March 01, 2022
Teams that collaborate around accurate data is an appealing concept - or is it an enterprise holy grail? Cloud data warehouses didn't solve the problem. Too many disparate data silos; too much digital exhaust. So where do we go from here?
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Tags: Analytics, AI, Big Data
Reigniting the analytics-to-decisions debate
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February 23, 2022
Analytics tools get shinier and fancier, but the classic problem remains: are we making better decisions? This is not a new debate. But in today's supposedly data-driven organizations, with hefty analytics investments in play, the issue takes on a new urgency.
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Tags: Analytics, AI, Big Data
Statistical bias in context - AI didn't invent quantitative methods of bias
diginomica.com
August 29, 2021
An effective approach to AI Ethics must reckon with bias, algorithmic discrimination, and privacy. These terms have a historical context that should be understood - if we want to deploy AI ethically. This time around, we delve into bias.
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Tags: Analytics, AI, Diversity and Inclusion
Trustworthy AI versus ethical AI - what's the difference, and why does it matter?
diginomica.com
August 29, 2021
We all want "trustworthy AI" - or do we? A closer look at the semantics of trust indicate the dangers of assuming trust is ethical. Fuzzy terminology will not help our pursuit of ethical AI.
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Tags: AI, Business Strategy, Diversity and Inclusion
The US National Security Commission issues its "Final Report on AI in Defense and Intelligence" - here are the takeaways
diginomica.com
August 29, 2021
The US National Security Commission has issued a massive, 700 page "final report" on the impact of AI on defense and intelligence. The report's conclusions are concerning, and not without controversy. US tech leaders were directly involved in this report - the proposed plan of action is worth a close look.
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Tags: AI, Security, National Security
How supercomputers found their industry mojo - the evolution of high performance computing
diginomica.com
August 29, 2021
Supercomputers used to be the domain of scientists and the military. Now the enterprise use cases are picking up steam. But in a way, all computers are supercomputers. Here's a look at how the field has evolved - and what's next.
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Tags: AI, Emerging Technology, Innovation
For John Snow Labs, doing good with NLP is in their DNA (and yours)
diginomica
March 02, 2021
Why was Dr. John Snow designated the "Father of Epidemiology?" His painstaking investigations of the outbreaks of deadly cholera in London in the 1850s led him to conclude that the disease was caused by contaminated water. His meticulous data gathering pinpointed the source at a single water pump.
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Tags: Analytics, AI, HealthTech
Metadata Shmedadata - today's approaches to metadata are inadequate, and that's a problem.
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February 23, 2021
Struggling with metadata is nothing new, but there's a misconception that advanced data tech and cloud storage solved this problem. That's not the case - so what is the way forward?
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Tags: Analytics, AI, Big Data
Data lakes, data lakehouses and cloud data warehouses - which is real?
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February 09, 2021
Cloud data warehouses aren't trendy enough - now we evidently need data lakehouses as well. But how should enterprises sort these terms? And has the data lake outlived its usefulness?
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Tags: Analytics, AI, Big Data
Moral licensing, AI teams, and you - a problem yet to be reckoned with
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February 05, 2021
Most of us have heard of cognitive bias - and the problem it can pose. Less well known is the practice of moral licensing. But it's an issue AI teams need to consider.
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Tags: Analytics, AI, Big Data
Robot empowerment - a viable alternative to Asimov's three laws of robotics?
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January 29, 2021
Human-robot interaction is upon us - we're in dire need of a framework that makes sense. Asimov's three laws of robotics are one model, but is it applicable to today's robots? An alternative based on robot "empowerment" is worth a close look.
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Tags: Analytics, AI, Big Data
How supercomputers found their industry mojo - the evolution of high performance computing
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January 20, 2021
Supercomputers used to be the domain of scientists and the military. Now the enterprise use cases are picking up steam. But in a way, all computers are supercomputers. Here's a look at how the field has evolved - and what's next.
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Tags: Analytics, AI, Big Data
Friday rant - Facebook's disinformation spreading, ad-server-economy must go
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January 15, 2021
Big Tech has been on the defensive lately, and for good reason. What was once perceived as a way to foster democracy has given way to algorithmic dystopia. But Facebook's algorithmic dangers are tied to an ad-server-based model we must dismantle. Rant time.
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Tags: Analytics, AI, Big Data
The problem of algorithmic opacity, or "What the heck is the algorithm doing?"
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January 13, 2021
Opacity in AI used to be an academic problem - now it's everyone's problem. In this piece, I define the issues at stake, and how they tie into the ongoing discussion on AI ethics.
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Tags: Analytics, AI, Big Data
Can fairness be automated with AI? A deeper look at an essential debate
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January 06, 2021
I've addressed whether fairness can be measured - but can it be automated? These are central questions as we contend with the real world consequences of algorithmic bias.
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Tags: Analytics, AI, Big Data
Can we measure fairness? A fresh look at a critical AI debate
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December 21, 2020
By now, most AI practitioners acknowledge the universal prevalence of bias, and the problem of bias in AI modeling. But what about fairness? Can fairness be measured via quantifiable metrics? Some say no - but this is where the debate gets interesting.
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Tags: Analytics, AI, Big Data
Musings on China's 'Global Initiative on Data Security' and the problem of security "back doors"
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December 15, 2020
A review of 'Global Initiative on Data Security' led me to an exchange with a company doing business in China. With new 5G security issues on the horizon, it's a good time to reflect on the implications of "back doors," ethical AI, and where the responsibility lies.
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Tags: Analytics, AI, Big Data