Category Archives: Complexity

Livable Income IN a Livable Economy (Part Two: the Impacts of AI)

Complexity, economic choice, Income, Income Inequality, Labour Force, Living Wage, Possibility, Poverty, Technologies

Last November I published a blog on the Edmonton CDC website and more recently repeated that posting here on Anticipate. Reading it first is, I suggest, of value to fully engage this posting.

The title of this posting reflects my interest in getting language “right.”

Living Wage and Livable Income are not synonymous. The latter includes the former and ensures we are considering those who do not earn wages and rely on pensions and/or government income security programs.  A livable economy is one that benefits society as a whole, not just those at the top of the income scale.

One of the biggest threats to a livable economy and the chance for people to have a livable income is technology and in particular Artificial Intelligence.

Artificial Intelligence (AI) is reducing the need for human intelligence and interaction. Systems and processes are fast becoming less reliant on human presence and more dependent on technologies that eliminate human error and/or just make things cheaper to do.

There are those who suggest that the disruptions caused by technologies are dramatically improving:

  • health for people; witness how much longer people are living (in the Western world in particular);
  • learning and education;
  • how we network and communicate;
  • convenience as in “Siri, how do you spell, perpendicular?” while offering us more choice (e.g. Skip the Dishes or Uber instead of just taxis);
  • the quality of products and services by eliminating human error; and
  • the bottom line by reducing labour costs and increasing profits.

We could debate the points above, but let’s assume all of the above is markedly accurate. Perhaps these are primarily positive impact of AI and other technologies, but the question for me has to do with the yin and yang of technological advances and their disruptive nature.

Technology proponents will point to the job creation that techno-firms provide and suggest that those jobs will replace the jobs lost because of technology. Some will admit there will be a structural skills gap in the workforce for a generation or so, but that everything will even out in the long run.

Maybe this evening out will happen over time, but it is hard to imagine that technology firms will be leading the way to structural reform that benefits workers who are being replaced.

Overall, it appears that technology is about the overall reduction of human workers in the market place. Currently much of this displacement is focused on low-skilled jobs, but don’t fool yourself. How long will it take robots to take these jobs:

  • Insurance underwriters and claims adjusters
  • Bank tellers and representatives
  • Financial and marketing analysts
  • Researchers
  • Inventory managers
  • Farmers
  • Taxi drivers and truck drivers
  • Bookkeepers
  • Lawyers
  • Pharmacists
  • Manufacturing workers
  • and more

If you believe technology will benefit you economically, you might be right, but overall the evidence to date indicates things don’t look so rosy down the road. Consider the following US data, based on a report about the impact of digital technologies on productivity and job growth —  in the MIT Technology Review.

The chart is a bit difficult to read but basically until 2000, the gap between productivity and employment in the United States has been fairly consistent and representative of a connection between jobs and productivity.  Since 2000, productivity has increased while jobs have pretty much remained at 2000 levels. That might be great news for big business, but far less so for workers.

Not only has the job trend not kept up with productivity, we can see a longer trend of significant GDP growth in the United States while household income has remained relatively flat since 1990. This chart indicates more economic achievement for the economy that is not benefitting workers at a corresponding rate, which frankly is one key factor in the significant income inequality that exists in the United States. Continue reading Livable Income IN a Livable Economy (Part Two: the Impacts of AI) →

To not be a racist you have to know you are a racist. 

Change, Complexity, Government, provocations, Racism, Upside Down Thinking

There’s so much I wish would change.

I am sure you feel the same way, too.

Problem is sometimes what I want to change are those that would, if they could, transform me into a variation of them. And, yeh, that’s about the same thing I want to do to them.

What is it about us that insists others should live as we want them to? Could it simply be arrogance or pride or that old self-aggrandizing, snide sense of entitlement? Why is it so many of us think the disenfranchisement of others is caused by some thing or somebody over there.?

I believe that who we are is a complex web of yin-yang attributes. Good and evil are coupled together. The same with love and hate. You get the picture. Who we are is about which we way we are pulled or influenced to lean. Sometimes we actually do not realize which way we turned or why.

Raise your hand if you are against racism. Continue reading To not be a racist you have to know you are a racist.  →

O Canada and the Mathematics of Change

Complexity, Data, Government, Human Rights, Learning, Movement, Possibility

I just read in the paper Canada is changing its national anthem to make it gender neutral though I prefer “gender inclusive.” Real change means changing our symbols and our icons when necessary to reflect society’s ever changing sensibilities.

I imagine there will be some kafuffle about this. Traditionalists will articulate traditionalist stuff, rationalizing where there is no longer rationale, if there ever was any. The reactions of many others will be something akin to a shrug of the shoulder or a 1-second read on Facebook, a click on Like, and a scroll down to a video of someone’s barking dog.

Some of us will sit before our humongous flat screens and  watch 4-headed debates that are a testimony to the betrayal of the word, “expert.”  I have never really learned anything listening to talking heads, other than the ends to which people will go to not make one whit of positive difference to what is happening in the world. Continue reading O Canada and the Mathematics of Change →

About Collective Impact: Types of Problems, Degrees of Change, Learning Loops, and Methods of Thinking

Change, Collaboration, Collective Impact, Complexity, Creativity, Innovation, Non-profit, Upside Down Thinking

Collective Impact is multi-sector approach to large-scale collaboration that is authentically inclusive of citizens in its development and implementation – in particular citizens who have life-experience with the big problems or issues being addressed, such as poverty, climate change, family violence, and so many more.

Collective Impact is not an approach aimed at creating program changes among a few agencies or undertaking collaboration in order to compete with other community initiatives. Rather, it tends to be focused on efforts to leverage talents, existing services, innovations, and resources in order to effect significant changes to policies and systems and where needed, significant programmatic changes. Such changes might occur within governments or government-run institutions, within education and health institutions, within business, or within service providers.

At recent sessions and workshops I held in Vancouver (Community Change Institute) and in Edmonton (Upside Down Thinking) , I shared a perspective on three types of problems identified by Brenda Zimmerman and how they connect to three types of change, three types of learning, and various types of thinking required in addressing each type of problem. My intent is to help our collective thinking about significant problems/issues facing our communities.

Simple problems are those we can fix easily and are sometimes called kaizen (the Japanese word for “continuous improvement”). Solutions to these kinds of problems are akin to tweaking a recipe or adjusting a process to improve quality or reliability of performance. Typically such changes are incremental. Continue reading About Collective Impact: Types of Problems, Degrees of Change, Learning Loops, and Methods of Thinking →

Democracy is dying. Time to get to work.

Collective Impact, Complexity, economic choice, Economy, Government, Income Inequality, Poverty

I came across an article by George Monbiot (www.monbiot.com) that appeared in the Guardian this July. In this article, Monbiot writes about James McGill Buchanan, an economist influenced by neoliberalism and deeply funded by billionaire Charles Koch, the 7th wealthiest person in the world.

According to Monbiot, Buchanan was an advocate for what he called the public choice theory. The general gist is that “society could not be considered free unless every citizen has the right to veto its decisions. What he meant by this was that no one should be taxed against their will. But the rich were being exploited by people who use their votes to demand money that others have earned, through involuntary taxes to support public spending and welfare. Allowing workers to form trade unions and imposing graduated income taxes are forms of “differential or discriminatory legislation” against the owners of capital.

“Any clash between what he called ‘freedom’ (allowing the rich to do as they wished) and democracy should be resolved in favour of freedom. In his book The Limits of Liberty, he noted that “despotism may be the only organisational alternative to the political structure that we observe.” Despotism in defense of freedom. Continue reading Democracy is dying. Time to get to work. →