Imagine deciding to eat nothing but chips, soft drinks and lollies for a month. At first, it might feel fun with a sugar hit here, a salty crunch there. After a while, you’d notice sluggishness, a foggy head, and a feeling of being a bit miserable. Your body can only handle so much junk food before things start to go wrong.
AI works on the same principle as “you are what you eat.” Instead of burgers and lollies, AI consumes data. Every email, court decision, contract template, and news article you feed into an AI system becomes part of its diet. If that data is of high quality, well-written, accurate, and relevant, the AI learns good habits. It suggests suitable contract clauses, identifies key risks in a disclosure document, and even drafts clear client emails. But if the data is messy, biased, or out of date, your “digital assistant” will reflect those flaws. You may end up with awkward wording, misleading advice, or worse, decisions based on outdated or unfair information.
A Cautionary Tale
Imagine a small firm using AI to speed up its document review. They loaded every case file they had with some neatly organised, but badly scanned pages with smudges, typos and missing paragraphs. The AI dutifully learnt from this messy mix. Its first suggestions looked plausible, but on closer inspection, it missed critical clauses and even invented page numbers that didn’t exist. The firm ended up spending more time correcting the AI than they ever would have on a manual review.
What went wrong? They’d given the AI “junk food.” Just as you wouldn’t survive long on chips alone, AI can’t thrive on bad data.
How to Set Your AI Up for Success
Here’s how you can give your AI the nutritious data diet it needs:
- Clean Up Your Data Pantry
Start by removing broken scans and duplicates by throwing out any files that are unreadable or appear more than once. Use consistent naming conventions like “Lease_Agreement_2024_v2” so the AI knows exactly what it’s looking at.
- Feed It Fresh, High Quality Information
Include up-to-date statutes, recent judgments and well-edited templates. Prune out material that’s no longer relevant or has known errors.
- Mix in Expert Supervision
Review its first drafts and correct mistakes; this shows the AI why those corrections matter. Provide feedback loops so the system gradually learns your firm’s standards.
- Watch for Bias and Gaps
Balance your data diet with files from a variety of matters, courts and jurisdictions. Spot check outputs for any sign of bias or missing content.
Test Your Data for High Quality
Before you feed any data into your AI, run these simple tests to ensure it’s up to scratch:
- Sample and Inspect
- Randomly pick 5 to 10 files from each data category (contracts, pleadings, emails). Manually check for clarity, completeness and correct formatting.
- Profile Key Metrics
- Completeness: What percentage of documents have all required sections?
- Consistency: Do dates, party names, and clause headings follow the same style?
- Accuracy: Cross-check a handful of facts (like court names and statute citations) against reliable sources.
- Error Rate Calculation
- Count the number of typos, OCR mistakes or missing paragraphs in a sample set. If more than 5 errors per 100 pages, flag that data as “junk” until corrected.
- Metadata Validation
- Ensure each document has clear metadata: author, date, and matter ID. Use simple scripts or spreadsheet checks to spot missing or mismatched fields.
- Bias Audit
- Look at the mix of cases by outcome, jurisdiction or judge. If 80% of your data comes from one court or type of matter, consider adding more variety.
- Feedback from Users
- Ask fee earners to rate AI suggestions on usefulness, clarity and accuracy. If they consistently score below “good” on a certain data category, revisit that dataset.
Measure and Adjust
Track time saved versus time spent fixing AI errors. Refine your data inputs until you see clear net gains in speed and accuracy.
The Bottom Line
Just as you’d nourish your body with a balanced diet, give your AI a steady supply of clean, diverse, accurate data. Feed it well, and it will return the favour by freeing you from routine tasks so you can focus on higher-value work and smarter strategic advice. But remember: if you slip back into old habits and feed it junk, you’ll end up right back where you started. Choose your data diet wisely!
