03 · What You Need to Know
What Makes AI-Generated Alt Text Accurate and Useful for Scientific Figures?
What Is Alt Text, and Why Do Scientific Figures Need It?
Alternative text provides a textual equivalent for information conveyed through an image. In HTML, it is commonly supplied through the alt attribute of an image element. Other document formats, including accessible PDFs and word-processing files, provide their own mechanisms for associating text alternatives with figures.
For readers using screen readers, alt text can identify an image and communicate information that would otherwise depend on visual access.
Scientific figures present particular challenges because their meaning often depends on axes, legends, statistical quantities, and relationships among observations.
A description such as "Graph of research results" provides little useful information. It does not identify what was measured or what the figure communicates.
The World Wide Web Consortium's Web Content Accessibility Guidelines require text alternatives for relevant non-text content, subject to the applicable success criterion and exceptions. The precise implementation depends on the image's purpose and context.
What Should Scientific Alt Text Communicate?
Effective alt text identifies the figure's purpose and communicates its essential information without requiring the reader to inspect the image.
For a scatterplot, this might include the variables represented on the axes and the principal visible relationship.
For a bar chart, it may identify the compared categories and the relevant difference.
For a scientific diagram, it may describe the major components and the relationships represented by arrows or other symbols.
However, the appropriate content depends on what the figure contributes to the surrounding article.
If the caption already explains the numerical results in accessible text, repeating every value in the alt text may create unnecessary duplication. If the figure communicates an important pattern not described elsewhere, that pattern may need to appear in the alternative.
The objective is to communicate meaningful information rather than mechanically describe every visible object.
What Can AI Reliably Identify From a Figure?
Multimodal AI can often identify familiar chart types and visible graphical elements, particularly when the image is clear and the layout is relatively simple.
It may recognize a scatterplot, histogram, box plot, heatmap, or forest plot and propose an explanation of the graphical structure.
However, recognition accuracy varies with image resolution, label size, figure complexity, and the model's capabilities.
AI may associate a legend entry with the wrong graphical series, misread a numerical label, or overlook a secondary axis.
Researchers should therefore verify every consequential element of the generated description rather than assume that correct identification of the chart type establishes complete accuracy.
How Is Alt Text Different From a Figure Caption?
A caption generally identifies the figure and provides information needed to interpret it within the research article. It may explain methods, abbreviations, statistical procedures, or experimental conditions.
Alt text provides an alternative for information conveyed by the image that is not otherwise available to the reader.
Figure caption
Provides scholarly context, definitions, and explanations associated with the figure.
Alternative text
Communicates the image's essential purpose or information when the visual presentation is unavailable.
These elements should complement one another.
For example, a caption may state that a figure presents regression coefficients with 95% confidence intervals. The alt text may communicate the principal graphical pattern or direct readers toward an accessible presentation of the estimates.
Researchers should avoid unnecessary duplication while ensuring that important visual information is not lost.
When Is Short Alt Text Insufficient?
Some scientific figures contain more information than a concise text alternative can reasonably communicate.
A multi-panel figure may contain several plots, different measurement scales, and multiple statistical comparisons. A heatmap may encode dozens of numerical relationships. A complex pathway diagram may show several interconnected processes.
Compressing all this information into one long alt-text attribute can make the description difficult to understand and navigate.
The W3C's accessibility guidance for complex images recommends providing a short alternative together with a more detailed text equivalent when necessary.
The detailed information may appear in surrounding text, a linked long description, or an accessible data table, depending on the content and publishing platform.
The broader task of creating accessible descriptions of research figures therefore extends beyond writing short alt text.
How Can AI Misinterpret Numerical Information?
Scientific figures often contain small tick labels, overlapping data points, transformed scales, and dense legends.
AI may estimate numerical values from graphical positions and present those estimates as exact results.
For example, a model might describe a correlation coefficient as 0.8 when the plotted annotation actually reads 0.08. Such an error could materially change the scientific meaning.
Researchers should avoid relying on image-based extraction when exact values are available in the underlying data, statistical tables, or verified analytical outputs.
When numerical details are necessary for the alternative, they should be checked directly against those sources.
Should Alt Text Report Statistical Significance?
Only when that information is relevant, supported by the research evidence, and appropriate to the description's purpose.
A visible difference between groups does not automatically establish statistical significance.
Likewise, overlapping or nonoverlapping error bars cannot always be interpreted as a definitive statistical test.
AI may use terms such as "significant," "strong," or "substantial" without a defensible statistical basis.
Researchers should verify the underlying analysis before including inferential claims in alt text.
Where the surrounding article already reports the statistical result, the alternative may focus on the visual information rather than repeating an extended interpretation.
Can AI Turn an Association Into a Causal Claim?
Yes. This is a consequential risk when AI attempts to summarize a figure's main message.
A scatterplot showing that students with higher engagement scores tend to have higher assessment scores does not, by itself, demonstrate that engagement causes better performance.
An AI-generated alternative stating that "greater engagement improves academic performance" would therefore be inappropriate unless the research design and evidence support that causal interpretation.
Alt text should preserve the distinction between observed association and demonstrated causal effects.
The same caution applies to pathway diagrams. Arrows may represent hypothesized relationships rather than empirically established mechanisms.
How Should AI Describe Uncertainty Intervals?
Figures may communicate uncertainty through error bars, shaded regions, or intervals surrounding estimates.
AI should not assume that all such displays represent confidence intervals.
They may instead show standard deviations, standard errors, credible intervals, prediction intervals, or another quantity.
When uncertainty is essential to the figure's meaning, the alternative should use the terminology established by the caption and analytical methods.
For a dense coefficient plot, a longer description or accessible table may be preferable to listing every estimate and interval within a single alt-text attribute.
What Makes Alt Text for a Heatmap Difficult?
Heatmaps encode values through color, often across many rows and columns.
An accessible alternative may need to identify the variables, explain the meaning of the color scale, and summarize important patterns.
However, the same colors can represent different quantities across figures. A red cell might indicate a high correlation, a large standardized value, or another measurement entirely.
AI should not infer the meaning of a color without reference to the legend or documented scale.
For a heatmap containing numerous important values, a structured data table may provide more complete access than a brief summary.
How Should AI Handle Multi-Panel Figures?
Multi-panel figures require careful attention to panel identity and relationships.
AI may confuse panel labels or combine findings from different analyses.
For example, one panel might display descriptive group differences while another presents model-adjusted estimates. Treating them as interchangeable would misrepresent the analysis.
Researchers should verify the content of each panel separately and decide whether the short alternative can communicate the overall purpose adequately.
If individual panels contain important information not explained elsewhere, a structured long description may be necessary.
Can AI Write Alt Text for Scientific Diagrams?
Yes. AI can draft descriptions of conceptual frameworks, process diagrams, system architectures, and other scientific illustrations.
The description should identify important components and explain the relationships that the diagram actually represents.
However, arrows and symbols may have discipline-specific meanings. A directional arrow might represent a hypothesized influence, a procedural sequence, or the movement of information.
Researchers should supply the intended meaning of these elements rather than allow AI to infer unsupported mechanisms.
Should Alt Text Describe Colors and Shapes?
Colors and shapes should be described when they communicate information necessary to understand the figure.
For example, if circles represent one instructional group and triangles represent another, that distinction may be relevant.
However, the precise decorative shade of a marker may not need description when its scientific meaning can be communicated more directly.
Researchers should avoid making essential information dependent on color alone.
Accessible visual design should also use suitable contrast, readable labels, and redundant encodings where appropriate.
Alt text complements these design practices rather than replacing them.
Can AI Generate Alt Text Without Seeing the Figure?
AI can draft a provisional alternative from a detailed description of the figure, its caption, or verified analytical information.
However, without access to the actual figure, it cannot confirm which visual elements appear or how they are arranged.
This limitation should be recognized when the task requires an accurate description of the image itself.
Researchers may provide a figure specification, data summary, or verified plotting output to support drafting, but the final alternative should still be checked against the published figure.
How Should Researchers Verify AI-Generated Alt Text?
Verification should focus on both scientific accuracy and accessibility.
Researchers should confirm that the description identifies the correct figure, variables, groups, units, and essential patterns.
They should check numerical and statistical claims against the original evidence and remove interpretations that the figure does not support.
The description should also be evaluated in the context of the surrounding text. It should provide necessary information without unnecessary repetition.
Finally, researchers should verify that the publishing system exposes the alternative through an accessible mechanism.
The challenge is not merely whether AI can explain a complex scientific figure. It is whether the resulting text functions as an accurate and usable alternative to the visual content.
