MDIA1003 Chap.9 The Future of PR and Advertising
The Future of PR and Advertising
Future communication practice combines changing media forms, interactive platforms, artificial intelligence and expanded measurement with enduring questions of authenticity, ethics and accountability. This chapter uses affordances and constraints to evaluate specific workflows rather than treating technology as an inevitable solution or threat.
Its closing method joins purpose, evidence, stakeholder remedy and the organisational capacity to revise or retire a system. Workflow mapping shows where sources, data, rankings and human judgment change the result. High-risk cases receive explicit referral routes, while monitoring compares resolution, equity, workload and harm rather than output volume.
Provenance, correction and review triggers make adaptability a continuing professional responsibility instead of a slogan attached to adoption. Application begins with a bounded communication task rather than a prediction about technology as a whole. Mapping the workflow reveals where evidence, ranking and human judgment enter, and therefore where safeguards or escalation belong.
A credible recommendation includes provenance, correction, evaluation and a retirement condition, allowing practice to change when assumptions or effects no longer hold.
What this chapter covers
- 01
Affordances and constraints arising between users, tools and environments
- 02
Interactive media that permit response within a designed framework
- 03
AI workflow analysis through inputs, decisions, outputs and affected people
- 04
Scope, provenance, privacy, accuracy, escalation and correction safeguards
- 05
Metric capture when available data quietly replaces the communication objective
- 06
Authenticity, adaptability and accountable professional judgment across changing tools
Worked example · free
Assess a fictional automated reply system
- 1Define the bounded purpose as locating published service information.
- 1Identify accuracy, language, privacy and high-risk referral failures.
- 1Require disclosure, source links, escalation, representative testing and correction.
- 1Evaluate resolution, equitable performance, workload and harm rather than reply volume.
Key terms
- Affordance
- A benefit or restriction arising from the relationship between a user and a medium, tool or environment.
- Interactive media
- Media that allow users to respond within a framework that can affect subsequent events.
- Automation
- The use of systems to perform or support tasks with reduced direct human execution.
- Provenance
- Information about the origin, transformation and custody of content or data.
- Metric capture
- A condition in which an available measure begins to replace the real objective it was meant to indicate.
The Future of PR and Advertising FAQ
How should communicators evaluate a new technology?
Define the communication purpose and workflow, then map inputs, decisions, outputs, affected people and failure modes. Assess benefits and constraints together. Choose safeguards, monitoring, escalation and remedy that match the consequences, and compare results with the objective rather than adoption or volume alone.
Does human review solve every AI risk?
No. Reviewers need time, evidence, authority and suitable expertise. Some errors are difficult to detect, especially across languages or biased data. Explain what is reviewed, which cases route to specialists, how corrections reach earlier audiences and who remains accountable when the system fails.
Why can more data produce worse communication decisions?
A visible metric may reward behaviour unrelated to the objective, such as clicks from misleading headlines. Data can also exclude groups or hide interpretation behind a score. Begin with the evidence need, examine validity and incentives, combine methods and record what the measure cannot establish.
Assessment move
Assess one communication technology through a six-part chain: purpose, affordance, constraint, affected group, safeguard and evidence. Keep the task specific and avoid general claims about all AI or platforms. Test whether the promised benefit is operationally verifiable and whether people can reach a human, correct an error or withdraw.
For dashboards, write the objective before viewing the metric and identify behaviour the measure might encourage. Record provenance, review decisions and rejected options. End each recommendation with the message the organisation can credibly make, the conduct needed to support it, the response route for audiences and a date or trigger for reassessment.
Draw the workflow from source material to output and mark every point where data, ranking or human judgment changes the result. Define high-risk cases that must route elsewhere. Test safeguards with intended users rather than checking only whether a button exists. Ask what happens when source pages change, a vendor withholds evidence or performance differs across languages and groups.
Compare reply volume with resolution, equity, workload and harm. Practise writing a retirement condition as well as an adoption case. Adaptability includes the ability to stop or redesign a system when its assumptions no longer hold.
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