nbcnews.com
Clanker": Internet Slur Highlights Growing Unease With AI
The internet slang term "clanker," originating from Star Wars, is rapidly becoming a common derogatory term for AI and robots, reflecting growing public unease about AI replacing human jobs and its increasing presence in daily life, as shown by rising usage on social media and even by a U.S. Senator.
- What is the significance of the term "clanker" becoming a popular online slur for AI and robots?
- The term "clanker," originating from Star Wars, is gaining popularity as a derogatory term for AI and robots, evidenced by its increased usage on platforms like TikTok and X, even used by Senator Ruben Gallego in a recent post about his new bill. This reflects growing societal unease with AI replacing human jobs.
- How does the use of "clanker" reflect broader societal anxieties related to AI and its impact on employment and daily life?
- The use of "clanker" mirrors historical slurs targeting marginalized groups, highlighting the anthropomorphization of AI and anxieties surrounding its advancements. This trend reflects a cultural need to express concerns about AI's societal impact, as seen in the high number of people preferring human customer service (64%) and those considering switching companies if AI is used (53%), according to a Gartner report.
- What are the long-term implications of using derogatory terms for AI, and how might this impact the development and acceptance of advanced technology?
- The increasing prevalence of AI and robots in daily life, from driverless cars to delivery bots, fuels the rise of terms like "clanker." This phenomenon is expected to continue, given the expanding use of AI and automation, leading to further societal discussions on AI's role and potential consequences.
Cognitive Concepts
Framing Bias
The article frames the story around the negative connotations of the slur "clanker" and the growing anti-AI sentiment. The headline and introduction immediately establish this negative tone, potentially influencing the reader's perception of AI before presenting a balanced view. The article emphasizes negative anecdotes and examples, such as the berating of delivery robots, reinforcing the negative framing.
Language Bias
The article uses the term "slur" repeatedly when discussing "clanker," framing the word negatively from the outset. While acknowledging that some consider it lighthearted, the overall tone leans toward presenting "clanker" as problematic. The use of words like "berated" and "harass" also contributes to the negative portrayal of interactions with AI.
Bias by Omission
The article focuses heavily on the emergence and spread of the slur "clanker," but it omits discussion of potential positive impacts of AI or counterarguments to the anti-AI sentiment. It mentions a Gartner report showing customer preference against AI in customer service, but doesn't explore the reasons behind this preference in detail or present alternative viewpoints. The lack of a balanced perspective on AI's role in society could mislead readers into believing the anti-AI sentiment is universally held.
False Dichotomy
The article presents a somewhat false dichotomy by focusing primarily on the negative aspects of AI and the use of the slur "clanker" without adequately exploring the complexities and nuances of the issue. While acknowledging some pushback against the term, it doesn't fully delve into the diverse opinions and perspectives on AI's societal impact. This oversimplification could lead readers to believe that the anti-AI sentiment is homogenous and uncomplicated.
Sustainable Development Goals
The emergence of the slur "clanker" to denigrate AI and robots reflects a growing unease with advanced technology and its potential impact on jobs and society. This unease disproportionately affects marginalized communities who may be more vulnerable to job displacement due to automation. The use of a slur, mirroring historical patterns of discrimination against marginalized groups, highlights the potential for technological advancements to exacerbate existing inequalities.