Core Viewpoint - The inevitability of AI failures necessitates that marketers recognize the potential severe consequences of overly promoting product advantages, especially in the context of AI. Companies must understand five key pitfalls related to AI before formulating marketing strategies to mitigate legal liabilities and brand reputation risks in the event of failures [1][19]. Group 1: AI Failure Case Study - In October 2023, a serious traffic accident involving an autonomous vehicle operated by Cruise, a subsidiary of General Motors, occurred in San Francisco. An independent investigation revealed that even a cautious human driver could not have avoided the accident, yet Cruise failed to report critical details about the incident [3][4]. - Despite not being at fault, Cruise faced significant repercussions, including a $1.5 million fine from the NHTSA, a $500,000 settlement, the revocation of its operating license in San Francisco, layoffs of half its workforce, and a more than 50% drop in company valuation [4][8]. Group 2: Public Perception and Responsibility - Research indicates that public perception tends to assign greater responsibility to manufacturers of autonomous vehicles compared to human drivers, even when the vehicles are not at fault. This bias persists across different cultural contexts [6][7]. - The "contamination effect" suggests that when one company's AI fails, other companies in the sector may also be viewed as having flawed systems, leading to a broader negative perception of AI technologies [8][9]. Group 3: Marketing Strategies and AI - Companies should emphasize their unique advantages, such as proprietary algorithms and safety measures, to differentiate themselves from competitors and mitigate the impact of potential failures [9][10]. - It is crucial for companies to communicate the presence of human oversight in AI decision-making processes, as this can reduce public blame on AI systems when errors occur [10]. Group 4: Misleading Marketing Practices - Overstating AI capabilities in marketing can lead to harsher public criticism when failures occur. For instance, Tesla's "Autopilot" branding has faced scrutiny for potentially misleading consumers about the system's actual capabilities [11][12]. - Research shows that consumers are more likely to hold companies accountable for accidents when products are marketed with exaggerated claims, highlighting the risks of misleading product naming [12][13]. Group 5: Human-like AI and Consumer Reactions - The use of anthropomorphized AI systems can lead to heightened consumer expectations and harsher judgments when failures occur. Studies show that consumers attribute greater responsibility to AI that appears human-like [14][15]. - In emotionally charged situations, the use of anthropomorphized chatbots can exacerbate customer dissatisfaction, suggesting that companies should be cautious in deploying such technologies in sensitive contexts [16]. Group 6: Ethical Considerations in AI Decision-Making - Public backlash can arise when companies are perceived to embed biases in AI decision-making processes, such as prioritizing certain groups over others in life-and-death scenarios. This indicates a need for ethical considerations in AI development [17][18].
当AI“翻车”，小心品牌被反噬