Signal Processing is Larger than its Beloved Name

Signal Processing is Larger than its Beloved Name

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Since its inception in 1948, the Signal Processing Society has evolved in pace with the many technological changes and advancements in our field. In its early days, our Society - the first and oldest among the IEEE Societies was known as the Professional Group on Audio of the Institute of Radio Engineers (IRE). Over the course of four decades, our name has changed a  few times from  “Audio“ to ”Audio & Electro Acoustics“ and then to "Acoustics, Speech, & Signal Processing“ and then to “Signal Processing” to reflect the field’s growth and diversity, becoming the Signal Processing Society, in 1989. 

Since then, our scope of interest has been revised twice to reflect new theories and applications, and many SPS technical committees have also changed their names. Our Society has also developed many new workshops, conferences and niche publications, journals, periodicals and outreach programs in an effort to celebrate the achievements of our members, strengthen our industry networking opportunities and also increase public awareness about signal processing.

We’ve made great strides, but our field is forever evolving with an eye on the future. Over the past few years, members have suggested that we’re perhaps due for another name change, that the term “signal processing” is obscure and doesn’t adequately capture the scope, range, dynamic nature and fundamental impact of our chosen field on so many facets of everyday life. We are certainly not alone in this dilemma. For example, the famous mathematical Stanislaw Ulam  wrote: “What exactly is mathematics? Many have tried but nobody has really succeeded in defining mathematics; it is always something else. Roughly speaking, people know that it deals with numbers, figures, with relations, operations, and that its formal procedures involving axioms, proofs, lemmas, theorems have not changed since the time of Archimedes.”

By comparison, our field is in its infancy, but it has grown and expanded rapidly to include many branches and sub-specialties. So, in December 2013, our society formed a committee headed by Petar Djuric to explore the possibility of a new name.

The committee wrote a wonderful blog post about this topic, soliciting member feedback, and listing nine previously suggested name changes:

1. Society on Signal Science and Engineering;
2. Society on Signal Processing and Data Science;
3. Society on Signal and Data Science;
4. Society on Signal Science and Processing;
5. Society on Data Science and Processing;
6. Society on Data and Signal Processing;
7. Signal and Information Processing Society;
8. Society for Data Science; and
9. Data Science Society.

Notice that  the term “Data Science” is in 5 of these 9 suggestions and “Data” is in six, but the word “Information” is in only one. 

The post elicited a lively discussion. Among the 50+ respondents, some favored a name change, and SIPS (Signal and Information Processing) was the most popular of the proposed names, favored by 21 respondents. Yet the majority of respondents (28) preferred to stick with our current name, saying that while it may not be inclusive of everything that we do, it’s the most succinct way to describe our complex, evolving field. Indeed, the very definition of a signal means the conveyer of some type of information, while the information within the signal is often related  to  knowledge and intelligence.

The respondents were certainly not unanimous that a name change would either increase or decrease our visibility among the general public, while also reflecting the monumental changes in our field since 1989. Whatever the ultimate decision, I agree with the recommendations that we would certainly benefit from improving the strength and clarity of our brand messaging, by articulating the impact of SP on so many fields, such as  finance, seismology, satellite communication, medical instruments and a wide range of commercial electronics and wearable technologies that billions of people use every day at work, at play, and, in almost every facet of communication.

Below are highlights from members’ responding to Petar Djuric's blog post about the name change proposal. I’m pleasantly surprised by the number and depth of these comments. It shows that this topic is timely and of great interest to our community. Signal processing is “present in nearly all the trendy mobile devices,” according to one respondent, yet it’s not well understood by our peers in science, industry, and the general public, “is oblivious to the concept.” It’s a fitting paradox for signal processing, which is described in the book Essentials of Digital Signal Processing as the “phantom technology because it is so pervasive and yet not well understood.”

Another respondent agreed, writing, “Signal processing is still a mystery to many of our peers, and it does not adequately reflect the current activities.” Others respondents pointed out that this dilemma hinders our ability to attract  good students to the field, negotiate promotions at universities and corporations, and “build a visible ecosystem” upon which individuals could envision a career. 

Diversity in our field can be viewed as both a blessing and a problem (curse? challenge?) .  A respondent wrote that our branding challenges “will get worse and worse with signal processing getting more and more diverse and intangible” as the emphasis shifts from boards and circuits to software applications. Yet, how do we strive to be both more inclusive and more succinct with our branding? Members suggested the addition of various qualifiers, the most popular of which were "data," "data science," "science," “signal science,” “engineering” and "information processing.”

The term ”data“ received a few favorables. With the increased emphasis and publicity on data in recent years, I wonder whether more responders would have favored this term had the blog been posted couple years later. Other respondents to the blog felt that while it’s currently trendy, and may have increasing funding opportunities, it may have a short shelf life and it’s too broad and generic, and too specific to computer science, data processing and "big data"  - implying all of which are poorly understood by the general public. There are also educational differences to consider. One respondent pointed out that while signal processing necessitates an advanced scientific education and carefully conducted scientific protocols, it only takes a few courses in computer science and web programming to become a “data scientist.”

The addition of "science" also received mixed reviews. As one respondent pointed out, “We are not scientists, we are engineers and I for one am damn proud to call myself an engineer." Scientists take things apart; engineers put things together. Not only are these fields different, they are polar opposites. Another respondent wrote, “Engineers is what we are, and signal processing is what we do.” Couple of respondents opposed the addition of "engineering" to our name. One respondent pointed out that engineering is also misunderstood by the public as dealing with work which signal processors do not do, such as work related to engines.

The addition of "information processing" was the most popular alternative among the respondents, primarily because it best conveyed the diversity of our field and our goal to “strive to be inclusive of all its members.”

Yet other members called information processing redundant, saying that you cannot process information, if it does not induce a signal; only signals that contain information can be processed and "signal processing" allows for information in a signal to be available in a “convenient format.” One respondent put it, "signal already indicates an information-bearing phenomenon, and 'signal processing' already encompasses the decoding/encoding of any kind of information.” However, I wish to add here that besides “processing,” much of our work involves understanding and learning about the systems we study.

Among the various proponents of maintaining our current name, respondents voiced concern that a name change would dilute the brand name. The term 'signal processing' is well established, featured in many journal titles, conference names and the majority of academic programs. University electrical engineering departments teach subjects with 'signal processing' in the title, and these courses are often first-year courses offered to undergraduates in Electrical and Computer Engineering, which piques the interest of young students, and sets them on the path to become signal processors. 

Other proponents pointed out that the Signal Processing Society is already a well respected brand in the science and engineering community. “Let’s keep the name and improve our outreach and publicity efforts,” wrote one respondent. Another member agreed, writing, “better outreach and publicity” will "fix this issue." However, instead of  “marketing the subtleties of a denoising algorithm that optimizes some super cool theoretical function, we should showcase the latest cutting edge technologies." Another member agreed, writing, “when people ask 'What is SP?", I say it is "everything that goes on inside a smartphone and their eyes suddenly light up.” 

“Whatever the new name of the Society, I will still say that I am a signal processing guy,” wrote one commentator. Another wrote, “'signal' must be kept since it represents the human instinct to communicate since the prehistoric age.”

Reading the comments on this blog has given me, a proponent of name change, much to think about. On one hand, a name change , e.g., by adding  the term 'Data Science,' would at present  help us increase our visibility and capture the interests of students, friends and other Societies, as well as the corporations and industries that provide employment and help fund our research and development. Our field has definitely evolved much further than processing signals measured by electronic devices and grew to processing, understanding and learning from data, irrespective to whether or not it is obtained from physical or physiological processes. Also, many of the concepts and theories we have advanced have been abstracted for use in a large number of applications. On the other hand, data science has much overlap with signal processing, mainly non-parametric, high-dimensional statistical signal processing (which involves big data and does not model the process.) Thus, it could be argued that 'Data Science' falls with the realm of SP. Furthermore, SP has now become much lager and diverse. It has permeated a vast number of technologies and applications. Watch for example, a brief video on "What is Signal Processing" for some examples of these applications. The scope of our journals range from speech to networks, from forensics to imaging, from biomedical to multimedia and so on. We have over 185 chapters in around 120 countries. This compels me to appreciate the good comments and relevant points made by the proponents of no name change and feel their devotion to the name. I consider myself fortunate that I have been working in this exciting field and am equally proud to be attached to our beloved “Signal Processing."

Let us continue this important discussion. Please add your comments on this page.