After over a year on Medium.com, I’ve finally took the time to build my personal blog. There were problems with Medium before, indeed, but the recent flood of fully Ai generated content was the final nail in the coffin. More profoundly, Medium consistently kept all my articles out of their search index that means, even if you were searching for the exact title, you would not find any of my articles.
This post was first published on Sept. 26 on the blog of the Linux Foundation for AI & Data under the title: Introduction to DeepCausality
The DeepCausality project was recently accepted into the Linux Foundation for AI & Data and, as the main author of the project, I want to use the occasion to share a brief introduction.
What is computational causality? Although deep learning roots in statistics, popular deep learning frameworks such as TensorFlow or PyTorch shield developers from the underlying math.
broader governing legislation establishing fundamental boundaries and a particular set of constraints that translate to technical enforceable limits.
The call for regulations by OpenAi’s Sam Altman[2] clarifies that the tech industry recognizes the existing vacuum that creates legal uncertainty. At the same time, the tech industry already adamantly opposes[3] the first draft of the European AI Act[4], citing overly restrictive measures as an obstacle to innovation. Eventually, all G7 nations will pioneer and pass legislation to govern artificial intelligence to safeguard widespread AI adoption; as Andrew NG stated in 2017, Ai will become the new electricity[5].
The prosperity paradox means that innovation destroys wealth while innovation also creates wealth. The late Clayton Christensen, who stipulated the dichotomy in his seminal work of the same name, was quick to point at an essential point of differentiation: Not all innovations are created equal. Instead, while innovation that increases efficiency diminishes prosperity, market-creating innovations create prosperity for a much more significant number of people.
Innovation is not strategy Innovation is the quest for novelty.
Innovation drives a lot of change within an organization and even across industries. However, the more change happens, the more resistance will emerge. Unavoidably, one key topic of innovation leadership remains the question of how to cope with resistance to change?
Robert Kegan stipulates that all resistance comes from the human mind and goes as far as conceptualizing a mental immune system that prevents some change while allowing for other changes.
In the 21st century, the most innovative organizations do not only rely on their internal workforce to innovate, but also on their supplier, partner, and even customer network to co-innovate successfully. Toyota successfully co-innovates together with its suppliers to improve its supply chain. Huawei Technologies co-innovates with large customers, suppliers, government, and regulators. In the process, the Chinese Telco company emerged as a leader in European telecommunications. In the new market-leading position, the previously forged partnerships with Governments and regulators work well for Huawei.
The rise of artificial intelligence to the new electricity of the 21 century raises valid concerns about machines overtaking human jobs. Human beings’ shortcomings become apparent when looking at increasing tasks specific super-human performance achieved by advanced artificial intelligence. Outspoken Ai critics quickly emphasize human intuition, empathy, and ingenuity as compensating traits. A weak argument considering the reality that many tasks artificial intelligence already has overtaken neither required compassion nor imagination.
In the digital age, coding is often seen as the most important skill for professionals thriving in the 21 century. However, while coding is undoubtedly important, it is not the only skill leaders need to succeed in the digital world. In fact, according to Harvard Professor Linda Hill, another skill is even more critical for success: Curiosity.
In a world where technology is constantly changing and evolving, leaders need to have a thirst for knowledge and a desire to learn and grow.
“When we are no longer able to change a situation, we are challenged to change ourselves.” — Viktor Frankl.
When a leader enters the safe zone, stagnation follows next. However, there is a thin line between optimal performance within a safe zone and peak performance outside a safe zone. Optimal performance, if well managed, can be sustained for a long time, whereas peak performance in leadership usually follows a crisis-growth-repeat pattern.
What do a submarine, an engine remanufacturing facility, and a steel factory share in common, and how does it drives innovation and profitability?
Let’s start with a submarine. The US Navy serves its mission to protect its home country by operating a fleet of several hundred ships. Due to the congressional mandate of full operational readiness, managing risk at the Navy comes down to enforcing battle-tested operational procedures. There is a manual for everything, and anyone who deviates from the strict operating procedures faces severe disciplinary actions for a reason.