ChatGPT has captivated audiences with its ability to generate remarkably human-like text. This advanced AI chatbot from OpenAI can draft everything from essays to fictional stories based on simple prompts within seconds. For brands and marketers, it promises to disrupt the content game.
Powerful as ChatGPT may be, integrating this AI tool responsibly is vital for maintaining brand trust and integrity. As Twitter guidelines state, all machine-generated content should be “produced ethically, transparently and with proper context.”
So how exactly should your brand use ChatGPT and similar AI for social media, blog posts, emails and other marketing content? Let’s explore crucial best practices.
Disclosing AI Content Origins and Context
The biggest priority is being transparent that your content was AI-generated. Make sure to prominently and explicitly disclose:
- Any post created fully by AI, such as a social media caption written entirely by ChatGPT.
- Hybrid posts combining AI and human writing input.
- Any AI-generated suggestions that were then reworked before being shared publicly.
According to recent Federal Trade Commission guidance, properly declaring when marketing content uses emerging technologies like AI chatbots is encouraged. Reviewers especially recommend using simple badges or plain language like “AI-written”, not vague corporate jargon that could confuse audiences.
Some brands opt to create branded badging like “Powered by AI” disclosed at the bottom of posts. Others directly state “The above was generated using the ChatGPT AI system” for complete clarity. Testing different approaches with focus groups can identify what resonates best with your audience demographic.
Keywords and Other Hidden AI Giveaways
While ChatGPT amazes with its eloquent long-form content on endless topics, it does still make subtle grammatical mistakes or include awkward phrasings at times if not thoroughly edited. These can serve as hints that a passage is machine-generated versus human-written.
Running posts through public AI text detectors such as WordTune’s tool can uncover these red flags. Brands should take care to refine any AI posts to avoid misleading audiences on the origins before publicly posting or distributing marketing emails.
Establishing Clear AI Governance
To deeply embed responsible practices, brands should institute internal governance surrounding if, when and how to appropriately utilize ChatGPT and similar AI generative tools.
Key elements to define upfront include:
- Approval workflows for AI-generated content before public distribution
- Limits on automating certain types of sensitive content topics
- Accuracy and plagiarism scanning procedures
- Criteria for when to involve human writers/editors in the process
- Explicit compliance rules around disclosing AI use with each piece of content
Having guardrails surrounding AI content creation further mitigates against potential PR backlash. It prevents cases where raw AI copy misses the mark tonally or includes factual inaccuracies before public posting.
Collaborative AI Tools for Governance
AI governance itself can be aided by AI. Startups like Anthropic provide platforms designed to keep AI models like ChatGPT transparent and safe through automatic version control, conversations logs and ethics reviews. Tools like Anthropic’s Constitutional AI assistant could facilitate auditing AI-generated content for accuracy, sensitivity and plagiarism.
Speech recognition providers like Rev.ai also offer detailed dashboards for managing AI usage, tracking costs and setting controls. Integrating these capabilities allows monitoring guardrails around ChatGPT content in real-time across an organization.
Blending AI With Unique Human Creativity
The most effective approach is combining ChatGPT’s raw generative writing capabilities with human strategy, ideas and refinement. This promotes innovation rather than fully automating the creative process.
Example strategies include:
- Using AI to rapidly generate 50+ headline options then perfecting the best 3-5 with human inputs
- Tasking humans on the content team with adding personalized examples, humor and lively data visualizations unavailable to AI systems
- Producing emotional brand stories and interview anecdotes that conversational AI cannot yet match
Such a methodology results in innovative, trustworthy content that plays to the strengths of both humans and machines collaboratively.
Promoting Responsible AI Literacy
To blend content capabilities optimally, creative teams should fostering understanding of core AI strengths versus limitations. Unfortunately research shows nearly 40% of business leaders still lack even basic AI literacy according to analyst firm Gartner.
Education around AI can be promoted through:
- Running controlled ChatGPT experiments to showcase abilities
- Circulating research on the state of artificial intelligence
- Conducting AI ethics training related to content specifically
Demystifying the technology’s promises and perils paves the way for creative experimentation within responsible boundaries.
Despite significant advances, AI chatbots like ChatGPT still contain underlying biases as well as gaps in knowledge that can lead to false information made public unless mitigated.
Always thoroughly fact-check any AI-generated content used in marketing emails or public platforms related to:
- Data, statistics and scientific claims
- News events, public figures and quotes
- Financials, product availability or pricing statements
- Policies, laws and regulations referenced
Such manual reviews are essential to guard against legal issues or undermining brand credibility in cases where ChatGPT’s statements are inaccurate or misleading. The goal is to catch any problematic passages before publication.
Uncovering Hidden Risks
What makes AI accuracy difficult is that machines can convincingly generate false statements. According to OpenAI, reactions by ChatGPT itself cannot fully determine what content it produces is misleading.
Additional tactics to uncover inaccuracies include:
- Running comparisons against verified factual databases
- Analyzing semantic context more holistically
- Tagging all unverified claims for human review
Ongoing investments to keep improving veracity and mitigating falsehoods will be key in advanced content AI.
Monitoring Evolving Best Practices
Any brand policies around using ChatGPT and AI for marketing should remain flexible and open-ended. The rapid pace of improvements in generative AI means continuous reassessment of ethical practices is required.
Content and social media teams should stay updated on elements like:
- Emerging third-party audits evaluating AI biases and risks
- Shifting public attitudes, concerns and cultural sensitivities
- New laws proposed regulating disclosure around machine-generated media
- Leading edge techniques for improving transparency and oversight
Regular tuning of internal guidelines will then best align with the latest industry expectations and societal norms still forming around AI-produced content.
Signs of Progress
Ongoing progress updates around ChatGPT versioning, accuracy and ethical safeguards should be monitored as well from developers like Anthropic. Recent research papersdetail enhanced techniques such as:
- Mitigating stylistic biases against particular demographic groups
- Improved citation and attribution when referring to source material
- Adding version tracking for better result reproducibility
Staying on top of the field positions brands to benefit from AI’s quick evolution.
Preparing Consumers for Our AI-Powered Future
Mainstream consumer perceptions around AI and machine learning remain polarized. Recent research from institutions like The Center for Media, Data and Societyshow the public is still largely divided on welcoming AI-produced media as part of our social and cultural fabric.
Brands play a key role in moving the needle positively by:
- Clearly communicating benefits around AI content creation without overstating current strengths
- Conveying the human role still essential for overall creative direction and strategy oversight
- Transparently sharing improvements to accountability, ethics and accuracy that build additional trust
Thoughtful integration of AI lays the groundwork for public acceptance both of individual brands leveraging the technology as well as emergent AI applications broadly across industries like media and academia.
Consumer Perceptions Around Synthetic Media
Certain content types and use cases also represent more sensitive areas the public remains concerned about in terms of AI generation. These include:
- Deepfakes and synthetic video/audio
- Computer-written fiction or editorial journalism
- AI-composed music
- Augmented creative works like art and poetry
Our recommendations focus on responsible marketing content from AI given current limitations. But anticipating where societal boundaries may shift over 5-10 years is prudent as capabilities accelerate.
The Outlook for Content Creation
Automated content production from AI promises to dominate marketing within just a few years. The pressing question now is how to guide this transformation positively.
As Microsoft’s Kate Crawford stated at Davos 2022 regarding the expansion of AI: “The most meaningful interventions will come from principled governance and oversight.”
Brands that proactively embrace essential ethics, accuracy and transparency practices for platforms like ChatGPT will emerge as leaders. They guide society towards an enlightened era where AI content spurs innovation while retaining public trust.
The Path Towards Responsible Synthetic Media
Much as Wikipedia evolved community guardrails after early quality concerns, similar social contracts around approving and validating machine-generated content will emerge.
Technical solutions currently in development also show promise for addressing thorny challenges like:
- Embedding metadata within AI media detailing provenance
- Watermarking synthetic content with manipulation scores
- Building centralized registries to identify fake media fingerprints
There remain obstacles before public acceptance. But anchoring creation within ethical frameworks paves the way for realizing AI’s potential while maintaining trust.