In July 2021, BlackEconomics.org released a Report Brief entitled “Black American Employment Representativeness.” We revisit that Report Brief here because the need to sound the alarm for Black labor is even more urgent today.
In addressing Black America’s employment representativeness, we focused on US Department of Labor, Bureau of Labor Statistics (BLS) statistics on employment by industry by race/ethnicity. Related data on employment by occupation by race/ethnicity are similar but provide additional clarity.
It is common knowledge that Black American workers are underrepresented in many important professional and technical fields. Therefore, we will devote our attention here to Black America’s over representation in selected occupations. We augment our earlier call for all relevant authorities to motivate shifts out of occupations in which Black Americans are over-represented by providing clear evidence concerning why these occupations should be abandoned.
The broad occupational classifications out of which Black Americans should shift are: (1) Transportation and material moving occupations (700,000); (2) Healthcare support occupations (500,000); and (3) Protective support occupations (200,000). The numerical values in parentheses are BlackEconomics.org’s estimates of the extent to which Black Americans are over-represented in these occupations.
Why should Black Americans exit these occupations?
The obvious reason is that technological developments will reduce the number of employees demanded in these occupations. We provide further clarity below.
• For Transportation and material moving occupations, technology is well en route to disrupting the industry. Specifically, for transportation in urban areas and long-haul trucking, autonomous vehicles will become the order of the day. Each day, the capture of procedural, functional, and logistical information increases, which can enable artificial intelligence (AI) and facilitate the handover of transportation to a driverless paradigm.
• For Healthcare support occupations, Japan continues to emerge as a leading developer of robots that can assist in the delivery of healthcare: From physically moving patients, to serving meals, to administering medications.
• For protective support occupations, visual technologies (cameras) and robots will increasingly replace humans who perform as police, security guards, and correctional officers. Privatization of these services and the need to ensure their profitability in a competitive environment will drive these outcomes.
In addition to the above-highlighted occupations, we issue a warning about another popular field for Black Americans—Education, training, and library occupations. Current educational performance, especially at the pre-K-12 levels, may appear to motivate greater demand for high-quality educators. However, expanded digital connectivity and evolving AI create an increasingly conducive environment for personalized (one-on-one) education. Education delivered through the just mentioned modality can reflect improved productive (cost cutting) efficiency.
We do not know precisely how rapidly these outcomes will unfold. However, this warning should be sufficient to permit those who want to shift to new occupations to secure and
capture them ahead of the developments that we forecast. Moreover, possible layoffs during a currently anticipated economic recession may present near-term opportunities to retrain and relocate to new occupations.
Importantly, those who are displaced by these predicted developments may find that a subsistence-level safety net (guaranteed basic income) may be erected in this newly evolving world. However, a life in near poverty that relies on that safety net will likely prove to be unsatisfactory.
Dr. Brooks Robinson is the founder of the Black Economics website: https://blackeconomics.org/
 Readers are invited to peruse the latest BLS statistics on occupations by race/ethnicity at https://www.bls.gov/cps/cpsaat11.htm (Ret. 091922).
 The relatively high cost of electric vehicles, which will be mandatory soon, and the high cost of lodging vehicles in urban areas is generating increased
demand for autonomous (driverless) vehicles (AV); see Associated Press (2022), “Driverless taxis are coming to the streets of San Francisco,” https://www.npr.org/2022/06/03/1102922330/driverless-self-driving-taxis-san-francisco-gm-cruise (Ret.092022). Also, long-haul autonomous vehicles are on the way; see CBS News (2020), “Driverless trucks could disrupt the trucking industry as soon as 2021,” https://www.cbsnews.com/video/driverless-trucks-trucking-industry-60-minutes-2020-08-23/ (Ret.
092022). Finally, given the increasing power of AI, we may find that passenger and freight rail services will be operated autonomously in the not-too-distant future—to the extent that they are not already.
 Japan’s expertise in robotization is advanced and well recognized. The country has opted to adopt automation over immigration to satisfy many of its need for labor to serve its rapidly aging population. See Bryan Lufkin (2020), “What the world can learn from Japan’s robots,” https://www.bbc.com/worklife/article/20200205- what-the-world-can-learn-from-japans-robots (Ret.092022). Prospects are bright for exporting this expertise to the US and elsewhere.
 Given expected advances in AI and robotics, security-related service occupations are ripe for automation. See Stanislava Ilic-Godfrey (2021), “Artificial Intelligence: Taking on a bigger role in our future security,” Beyond the Numbers; https://www.bls.gov/opub/btn/volume-10/investigation-and-security-services.htm (Ret.092022).
 The COVID-19 Pandemic provided a natural laboratory for educators to assess the efficacy of online instruction broadly. While recent test results indicate that students “suffered” from online instruction delivered during the pandemic, information about who suffered and why is now available and can enable educators to modify their approaches to delivering online instruction. In any event, when properly configured, it is difficult to argue against the likely benefits and effectiveness of one-on-one (master/mistress-to-pupil) instructional arrangements that are possible using AI online—whether delivered in homes or in classroom settings.