As an integral part of the San Francisco Giants’ culture, sports broadcasters Mike Krukow and Duane Kuiper represent one of baseball’s greatest bonds. Despite rich playcalling and immense knowledge, they represent a dying breed. With the advent of artificial intelligence, sports journalists risk losing their jobs to efficient algorithms. These algorithms can compute statistics on the spot, analyze gameplay, and craft journalistic pieces ranging from articles, to videos and live broadcasting. Despite putting a cultural keystone of baseball aside in sports broadcasting, new AI technology will prove to have many advantages over traditional sports journalism due to its usage of empirical evidence, reduction of bias, and efficiency.
Artificial Intelligence does pose one huge advantage to the industry of sports journalism: the ability to do quick calculations on the go. While most articles include minimal information about statistics or odds, AI can add a more analytical perspective to journalism and help the sector become more evidence-based as opposed to subjective responses to visual events. As journalists inevitably introduce bias through their perspective, AI can help bring an objective truth into play. For most readers, a balance of subjectivity and objectivity is necessary to good journalism. Currently, the sector needs more objectivity as opposed to more opinionated writing. This blend is more achievable with advanced statistics calculated on the go by AI programs.
The reduction of bias is a crucial addition that AI brings to the table. AI lacks subjectivity and uses evidence and findings to come up with a definitive answer. It doesn’t have ties or relations to certain teams or players that predetermine or hinder its decisions. Lacking bias in sports is essential as it gives the audience definitive information with proof, as opposed to claims which lack evidence. Aside from this form of bias, it will also cover a larger range of sports as opposed to just the most popular ones. AI will also cover a more wide range of sports as it can easily write and generate evidence and graphics. Because of this, it can cover all sports evenly and be more fair to sports who lack coverage. By doing this, AI caters to a larger audience and gives all readers of all sports information they need.
But what does generating articles mean? Algorithmic journalism is a process in which an article is created by a code or piece of software using artificial intelligence. For example, while a journalist might summarize a sports event, algorithms will only cover parts of an event that are more crucial and are able to easily distinguish the highlights of an event. For example, during the Wimbledon Tournament in 2023, AI was used to algorithmically generate highlight reels for matches and successfully determine important parts of the game. In this concept, AI will not only write and create content, but eventually be used to do in-game commentary and mimic commentators for efficient reporting during live matches. The AI will also work alongside professionals in some situations, as proposed by the idea of AI and human commentators working together in sports broadcasts.
Efficiency is also an essential aspect of sports journalism. Sports journalism is best consumed in a quick fashion. It is about concision and getting information to readers in the most efficient way possible. AI will optimize summaries of games with an efficient balance of concision and precision, which essentially renders beat writing defunct. These programs can take statistics and implement short sentences with graphics in mere seconds, as opposed to hours or days of human work, in order to get points across to readers. Not only is this a threat to manually written journalism, but also, in video content format, of TV sports news outlets. Why even air segments on sports when we can effectively convey information in a more distilled format? Algorithmic journalism serves a more potent medium for news consumption.
Though many might think of data as strictly numbers, data conveys a story to an audience. When we see a player perform in the 15th percentile one year and the 99th the next year, we can look at individual statistics to see where that player improved. Along with context and some detail in writing, we can make stories from data and not vice versa. Not only can data be more reliable than human sources, but can even be more human at times with the stories they tell about athletes and their improvement of change over time. Not only is data some of the most important information in current sports journalism, it is currently shaping the sector. Instead of relying on words of sources, we can take data and prove things without merely discussing them in articles. However, some variance may occur depending on how the data is interpreted. Journalists can not only pose solutions or problems in articles, but with data they can solve important problems and make reasonable claims. Credibility is more assured in statistics as opposed to word of mouth. A person's opinion is subjective while data is always objective and can point to real and concrete claims and ideas.
When looking at numbers, AI can easily detect trends in data and point them out, adding new perspectives to the articles it creates. However, though AI adds new aspects to the sector, it kills many jobs too. Most sports journalists won’t be able to directly compete with calculations done by AI. On the other hand, a high number of jobs are also created in statistics and sports analytics roles for publications. These AI programs need developers behind them and mathematicians who can help guide their findings. With open spaces for programmers and mathematicians, the sector can take losses in one category of jobs and replace it with another which goes hand in hand with it. Though they require different credentials and pathways, over a long period of time, many people who work in sports journalism will become analysts who use calculations to back their claims and refurbish software used to produce content.
An argument commonly talked about against AI is the idea that it dehumanizes a whole sector. Many people feel as though AI makes opinion writing obsolete and that it kills the human thinking that makes opinion articles unique. They feel as though AI does not have emotion or subjective thoughts, or that it does not have the capability to make clear cut column articles. However, AI does more for opinion articles than humans do. When humans write opinion articles, they often lack the data or evidence to clearly back up their perspective, hence why opinion many times lacks sources in writing. The counter to this however, is that AI can make subjective claims using data and evidence it detects. So instead of a subjective opinion article, it does more of a synthesis or analysis and creates a prediction or opinion based solely on factual information it knows to be true. Not only does this make AI more credible in this case, but it makes it more accurate as well.
Though with all of this, credibility is still a discussed issue. Many feel as though AI programs who may source data internally or from an external source may not be getting information from the right place or be interpreting it incorrectly. To do this, Algorithmic journalism must work towards putting sourcing within articles or content and also have inbuilt fact checking code programmed by their developers. To do this, data sources should be given to the audience and step by step access information should also be provided to readers. By giving all readers access to their information, news outlets can prove their credibility and also give others access to information and other articles which can enrich their opinion on a given topic. Also, readers who enjoy looking at the data and making their own visualizations may also benefit from easy accessibility to said data.
One issue that many also point out about super efficient AI summaries and content in general is that they compete with TV and outlet viewership and overall sales. One solution might be making summaries overly concise so that if one is intrigued, they still lack the information to feel completely knowledgeable on a specific sporting event and feel the urge to watch the next game or the full highlights. By doing this, we can incentivise viewership by talking about specific plays or parts of a game and intriguing viewers without telling them the whole story. Similar to a “cliffhanger”, this attribute may make more people watch TV instead of negatively affecting viewership.
In addition, AI might lack the proper information to understand credible sources for its articles. It may take data from sites that lack credibility and could possibly mislead viewers. This is why I see the need for a new system: for example, A board of sorts which marks a seal of approval on certain sites which are credible for AI to take information and data from when writing articles. In this case, the board should organize a database in which cross checked data is stored and AI can take information and evidence from clearly credible sources as opposed to having to traverse the open internet. Another option may be limiting information to only league websites for data and allowing AI to use the open internet for synthesis pieces only so that they can find unique perspectives and ideas to enrich their content. By doing this, we prioritize reliability while also preserving the AI’s freedom to sift through endless (possibly incorrect or rash) information to create more subjective pieces as well.
AI does additionally lacks the ability of good storytelling. It lacks the narrative skills that may add personality to articles and to certain anecdotes. And when AI has anecdotes or speaks from a more human perspective, there is an artificial feel to the way it writes. Even if it writes beautifully, we know that an algorithm created the somewhat human experience we had just read and that a piece of software never had those memories.
In summary, AI and algorithmic journalism can revolutionize the way we consume sports journalism content and the way we get information in our day to day lives. In the future, we can expect AI to take over many sports websites and also create content in the form of video and audio. Currently, Google is among one of many companies experimenting with their new article writing tool that will eventually have the capabilities to replace human-written journalism. Their work is put into engineers who develop tools.
Though threatening to many jobs, a much larger opportunity in sports journalism rests just beyond the horizon ready to be implemented in coming years. By turning one of the most human and possibly subjective subjects in the world into a robotic and algorithmic process, AI has shown humanity that it has no bounds in its applications. But alongside its possible widespread application, AI will still depend on humans for much of its work and sports journalism will remain a very human field.