Category Archives: communication

Are We Racists?

BMAI friends. The following ramble is my first cut at making sense of the grave role racial (and other) bias is playing in the world today. This was prompted by comments I see daily from my family and friends on social media. Thinking about the great lack of self- and group-awareness many of the commenters display, I turned my scope inward. How do my own innate, evolved biases slant me to take my group’s and my own privileges for granted and make invalid assumptions about those I perceive (subconsciously or explicitly) to be ‘the other’? I put this forward to start a discussion and hope you will contribute your own insights and references. Feel free to post comments or even insert questions, comments, or new text directly into my text. Of course, you can create your own new posts as well. Thanks.


Two Levels of Racism
 
1. Population Group Level
 
Racism is an expression of group dynamics. Consider two levels of racism. First, there’s systemic racism where conditions in a population generally favor one race over others. One race (or maybe a few races) has greater access to material and cultural influence in the population. This does not occur accidentally, but through the ongoing efforts of the dominant group to achieve and expand its controlling influence.
 
2. Individual and Local-Group Level
 
That’s where the second level of racism comes in. How a person perceives any group’s efforts to attain equal access and influence depends on whether the person is in the dominant group or the aspiring group. There are many ways individuals and their affinity groups perceive and act within the racially unequal system to maintain or change the racial inequalities. The group in power perceives efforts in its favor as good, appropriate, justified, patriotic, necessary, ethical, moral, and even (when there’s a shared group supernatural narrative) ordained, holy, etc. When a member of an out-group appears to support (or at least not outwardly oppose) the in-group’s dominance, members of the in-group view that as a proof that they are rightfully on top.
 
The group in power perceives any questioning of its dominance in the larger population as suspicious, dishonest, lazy (attempts to gain more access than is deserved), subversive, unpatriotic (or even treasonous), or (through the lens of dogma) evil, anti-God, etc. Obviously, racism (and other efforts to maintain inequality) is at work when these perceptions are acted out by legislators, law enforcers, prosecutors, juries, judges, presidents and their staff members, the private sector, and individual members of the favored group.
 
Members of a group with less influence perceive their questioning of the dominant group’s power in opposite terms from how the dominant group sees their struggle. Members of lower-access groups experience their quest for equality on all fronts as expressions of their inherent right–even necessity–to pursue “life, liberty, and happiness.” They see the efforts of dominant groups to control and exclude them as unjustified oppression by people who abuse the power provided them within a biased system that clearly needs to be changed.
 
On the first (population) level, racism is an aspect of the in-group/out-group dynamics that are present in all of us. Our ‘hard-wired’ programming is to subconsciously favor those we perceive to be more like us (in outward appearance, views, and culture) and subconsciously feel some degree of aversion and suspicion (and often fear) of those whose appearances, views, and culture vary from ours. Groups (through the actions of their members and leaders) use their power to slant social and economic systems to favor their own power and influence and to decrease the influence of those they perceive as not members of their group(s). When this natural bias results in one racial group having greater access to resources (education, healthcare, emergency services, and other public services; jobs; legislative influence; judicial equality; media visibility; etc.), systemic or structural racism is in place.
 
A takeaway of all this is that we are all racists, in the sense that the human brain has evolved complex social navigation functions that include strong biases in favor of one’s perceived in-group and disfavoring members of all other groups. To the extent we are hard-wired to perceive people who (as a category) look superficially different from us as somehow less safe or worthy of inclusion and power-sharing, we are innately racist. When we make the effort to become aware of, challenge, and ensure our racial biases do not influence our words and actions, we are moving toward a less bigoted way of being.

There’s no such thing as a male or female brain

See this New Scientist article. Excerpt:

When the group looked at each individual brain scan, however, they found that very few people had all of the brain features they might be expected to have, based on their sex. Across the sample, between 0 and 8 per cent of people had “all-male” or “all-female” brains, depending on the definition. “Most people are in the middle,” says Joel.

This means that, averaged across many people, sex differences in brain structure do exist, but an individual brain is likely to be just that: individual, with a mix of features. “There are not two types of brain,” says Joel.

Collective Enlightenment Through Postmetaphysical Eyes

The paper can be found here. The abstract follows:

Enlightenment has had broadly different definitions is the East and West. In the East it is seen as an individual accessing meditative states that transcend the world of form in a metaphysical reality. In the West it is more about individual development to abstract reasoning, which can accurately represent empirical reality but is itself an a priori, metaphysical capacity. Enlightenment in either case is based on metaphysical individual achievements. However the postmetaphysical turn has questioned such premises, instead contextualizing both meditative states and abstract reasoning within broader socio-cultural contexts. Enlightenment itself has thereby been redefined within this orientation and is seen more as a collective endeavor that is collaboratively enacted.

Should AI agents’ voice interactions be more like our own? What effects should we anticipate?

An article at Wired.com considers the pros and cons of making the voice interactions of AI assistants more humanlike.

The assumption that more human-like speech from AIs is naturally better may prove as incorrect as the belief that the desktop metaphor was the best way to make humans more proficient in using computers. When designing the interfaces between humans and machines, should we minimize the demands placed on users to learn more about the system they’re interacting with? That seems to have been Alan Kay’s assumption when he designed the first desktop interface back in 1970.

Problems arise when the interaction metaphor diverges too far from the reality of how the underlying system is organized and works. In a personal example, someone dear to me grew up helping her mother–an office manager for several businesses. Dear one was thoroughly familiar with physical desktops, paper documents and forms, file folders, and filing cabinets. As I explained how to create, save, and retrieve information on a 1990 Mac, she quickly overcame her initial fear. “Oh, it’s just like in the real world!” (Chalk one for Alan Kay? Not so fast.) I knew better than to tell her the truth at that point. Dear one’s Mac honeymoon crashed a few days later when, to her horror and confusion, she discovered a file cabinet inside a folder. A few years later, there was another metaphor collapse when she clicked on a string of underlined text in a document and was forcibly and instantly transported to a strange destination.

Having come to terms with computers through the command-line interface, I found the desktop metaphor annoying and unnecessary. Hyperlinking, however–that’s another matter altogether–an innovation that multiplied the value I found in computing.

On the other end of the complexity spectrum would be machine-level code. There would be no general computing today if we all had to speak to computers in their own fundamental language of ones and zeros. That hasn’t stopped some hard-core computer geeks from advocating extreme positions on appropriate interaction modes, as reflected in this quote from a 1984 edition of InfoWorld:

“There isn’t any software! Only different internal states of hardware. It’s all hardware! It’s a shame programmers don’t grok that better.”

Interaction designers operate on the metaphor end of the spectrum by necessity. The human brain organizes concepts by semantic association. But sometimes a different metaphor makes all the difference. And sometimes, to be truly proficient when interacting with automation systems, we have to invest the effort to understand less simplistic metaphors.

The article referenced in the beginning of this post mentions that humans are manually coding “speech synthesis markup tags” to cause synthesized voices of AI systems to sound more natural. (Note that this creates an appearance that the AI understands the user’s intent and emotional state, though this more natural intelligence is illusory.) Intuitively, this sounds appropriate. The down side, as the article points out, is that colloquial AI speech limits human-machine interactions to the sort of vagueness inherent in informal speech. It also trains humans to be less articulate. The result may be interactions that fail to clearly communicate what either party actually means.

I suspect a colloquial mode could be more effective in certain kinds of interactions: when attempting to deceive a human into thinking she’s speaking with another human; virtual talk therapy; when translating from one language to another in situations where idioms, inflections, pauses, tonality, and other linguistic nuances affect meaning and emotion; etc.

In conclusion, operating systems, applications, and AIs are not humans. To improve our effectiveness in using more complex automation systems, we will have to meet them farther along the complexity continuum–still far from machine code, but at points of complexity that require much more of us as users.

People’s brains store and recall stories the same way

New scientific findings support the idea that different humans’ brains store and recall story scenes the same way, rather than each person developing unique memory patterns about stories. Also, people generally do well recalling the details of stories. I want to see more targeted research that determines whether information packed in story structures (a person wrestling with a difficult challenge and changing as a result) is more readily and accurately transmitted from brain to brain via storytelling. This would be compared with information packaged simply to inform of facts (Wikipedia entries, technical reports, etc.). My experience agrees with this research: different people tend to recall stories equally well. (Oddly, people vary greatly in their recall of eye-witness tasks. Something about how information is delivered in storytelling greatly improves accuracy of recall.) I think our brains evolved a special facility for paying attention to stories and therefore to remember them. If true, storytellers should learn what we can about how the brain processes stories.