4 Reasons Advertisers love Generative AI, and 5 Reasons they Hate It
- Personalization – Generative AI has the ability to generate personalized content that aligns with the tastes and responses of the intended audience, thereby increasing the pertinence and attractiveness of the advertisements.
- Efficiency and Time-Saving – Generative AI can streamline the creation of ad campaigns, and produce multiple versions of advertising content for testing, lessening the amount of time and labor necessary for human marketing professionals.
- Cost-Effective – Generative AI can produce superior content (without human designers, photographers, or content creators) and can enhance the efficiency of ad expenditures by identifying the most suitable channels and formats tailored for each advertising campaign.
- Increased ROI
By enhancing the performance and conversion rates of promotions, generative AI can assist marketers accomplish superior business outcomes and offer valuable suggestions and insights derived from data analysis and market trends.
Dangers of Generative AI
- Hallucinations — AI models, despite their advanced capabilities, are susceptible to errors known as Hallucinations. Unlike humans, they lack human-like understanding and heavily rely on training and data to generate responses. Interacting with an AI chatbot often leads to experiencing these hallucinations, whether due to a misinterpretation of the input provided or the bot providing blatantly incorrect answers to questions.
- Deepfakes are deceptive creations of videos, photos, and voice recordings that mimic the appearance and voice of real people. Exploited in various malicious ways, they have been deployed to target public figures like celebrities and politicians, disseminate misleading content, establish fictitious identities, and compromise genuine accounts through unauthorized access and infiltration.
- Data Privacy – Generative AI raises privacy concerns as it typically involves storing user data for training models, and employees can inadvertently expose sensitive and proprietary enterprise information while engaging with generative AI chatbot solutions, resulting in security breaches.
- Cyber Security – Generative AI models, with their advanced abilities like coding, present a potential risk if they end up in the hands of malicious individuals, leading to cybersecurity issues. These bad actors can exploit the models to generate malicious code by employing sophisticated social engineering and phishing techniques. The security measures implemented by generative AI vendors are often difficult to verify, further exacerbating the concerns surrounding the misuse of this technology.
- Copyright is a big concern because AI models learn from the internet and can use that information to create new content without permission. This is especially problematic for AI-generated art like photos and music. Since it’s difficult to know which works the AI models learned from, addressing copyright issues becomes challenging.