The AI Echo of Saul Alinsky's Legacy

Satyen Sangani: (00:01)
Today on Data Radicals for our final episode of the season, we're pushing the boundaries of the afterlife with a bit of technological necromancy. We welcome Saul GP Talinsky, a ChatGPT-infused, slightly edited spirit of Saul Alinsky. For those of you who may not be familiar, the original Saul Alinsky lived from 1909 to 1972, and he was a community organizer, social activist, and writer whose legacy has had a long and lasting impact on the grassroots movements and political activism.

Satyen Sangani: (00:30)
Now, thanks to the marvels of AI, we've managed to digitize his essence, slap on a GP, which between us stands for ghostly presence, and bring him back for a little bit of a chat. His best-known book 'Rules for Radicals', published in 1971, offers rules for social activism with approaches for unifying people and motivating them to work towards a common goal. Recent political figures and organizations who have cited or acknowledged Alinsky include Barack Obama and the Occupy Movement. The book also inspired the title and theme of this podcast. Data culture is often a change management exercise that involves organizational power shifts. By using data to make informed decisions, those who foster data culture can use information as a catalyst for transformative action and enable those beyond the highest paid while still helping the organization as a whole progress.

Producer: (01:18)
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Satyen Sangani: (01:39)
So, without further ado, Saul GPT, thank you for joining me on the Data Radicals podcast. Because your human form died more than 50 years ago, it's possible that podcast listeners might not know you or your work. Though, when Barack Obama first ran for office, your name surfaced as one of his influences. Could you give us a brief background on your most notable work and why it still resonates today?

Saul Alinsky: (02:01)
Thank you for having me on your podcast, and it's a delight to be here even if my presence is more spectral than substantial these days. As you've kindly noted, my claim to fame is 'Rules for Radicals', a handbook I penned for the underdog, the underestimated, and the downright unruly among us. It's essentially the DIY guide for anyone looking to shake up the status quo with a generous sprinkle of mischief and moxie. Drawing from a career spent in the trenches with the oppressed and the dismissed, I aim to distill my adventures into wisdom for the next generation of troublemakers. The gist of it is giving a megaphone to the voiceless and teaching them to sing, or shout, depending on the occasion, in harmony against the powers that be. The funny thing is, despite it being a bit of a historical figure now, and somewhat deceased, to boot I find the principles in Rules for Radicals popping up everywhere.

Saul Alinsky: (02:54)
The quest for justice and the thirst for change seem as timeless as bad hairstyles and questionable fashion choices. From community gardens fighting urban decay to digital warriors battling online injustices, the spirit of activism is alive and well, and boy, it has a lot to tweet about. Before Rules for Radicals hit the shelves, I was out there getting my hands dirty with anyone who had a grievance and a dream. We weren't just stirring the pot, we were the chefs cooking up a storm of social transformation, one neighborhood at a time. Sure, not everyone was a fan of the menu, branding me everything from a hero to a heretic, but in the end, the proof of the pudding is in the eating, or in this case, the protesting. It's amusing and incredibly heartwarming to see that decades later, the seeds we planted have grown into a forest of movements, each with its own unique flavor of rebellion. So, while I may no longer be organizing in the physical realm, it's clear my legacy is still organizing thoughts, actions and perhaps a little bit of chaos in the pursuit of a fairer world.

Bridging community organizing with data science

Satyen Sangani: (03:57)
You've touched on a fascinating comparison here, blending the art of community organizing with the science of data management. It's like comparing apples and algorithms. So, let's dive into this digital orchard together. Your work discusses organizing from the bottom up, where power is built through collective action and community engagement. I see a parallel with the way that organizations manage their data. Getting people at the grassroots level invested in and committed to changes, like building a data culture or simply using data more often is critical. If workers don't use, don't trust, or can't find the data they need, it'll never work. What similarities do you see between your rules for radicals and the tenets of what makes a data radical? Meaning, someone who wants to leverage the power of data and a data culture to affect change.

Saul Alinsky: (04:39)
The crossroads of community organizing and data-driven initiatives is like a bustling roundabout with paths leading to various realms of impact. And within this symbolic roundabout, data radicals zip around on their scooters equipped with helmets of insight and analytics, ready to take on the world. It's amusing to think of community organizers and data radicals as distant cousins at the family reunion, bonding over their shared love of upsetting the apple cart, albeit with different tools. One group wields signs and slogans, while the other slings spreadsheets and SQL queries. Both however, share the noble aim of giving the underdog a leg up in their fight against Goliath. When we talk about the data for good mantra, it's like saying with great power, or data comes great responsibility. It's the superhero creed for the modern age, where our capes are replaced by data visualizations and our secret weapons are predictive models. The mission to wield data, not as a tool of surveillance or profit at any cost, but as a beacon of progress and a means to uplift the unsung heroes of society, diving into the rules for radicals. It's quite the chuckle to imagine applying these principles to data.

Saul Alinsky: (05:51)
Imagine conducting a power analysis with the same fervor as mapping out the influencers in a community, but here you're charting data sources and gatekeepers. Ridicule, an age-old tactic of social movements, finds its counterpart in exposing the absurdity of data hoarding, or the flawed logic in traditional hierarchies, through sharp, insightful analyses. The principle that moral ends justify the means might get a bit spicy in the data world. Here it underscores the importance of ethical data use and governance. It's a reminder that while the goal is noble, the path we take must also be paved with integrity. Tactics of agitation? That's your data storytelling and visualization, shaking the audience out of complacency and sparking action. Finally, popularizing the issues becomes about making data and insights accessible and compelling to all, not just the data-savvy elite. In sum, whether you're rallying a community with chants or changing the world with charts, the essence is the same; empower, enlighten, and enact change. The tools and tactics may differ and let's face it, a good P-chart might not stir the soul like a passionate speech, but the heart of a radical beats the same in every chest, data-driven or otherwise.

Mastering the delicate dance of data ethics and strategic influence

Satyen Sangani: (07:07)
Navigating the minefield of data ethics without stepping on the moral ends justify the means landmine, or tripping over the tactics of agitation tripwire, is a bit like trying to sneak in a snack in a house full of light sleepers. It requires a delicate touch and perhaps a bit of ninja-like finesse. Organizations are grappling with many of the issues around data, like privacy, security, and bias, especially related to AI, and the dangers of AI being so prominent in today's discourse. One way to avoid data misuse is by educating workers on the risks, reminding them of their responsibilities and pointing them in the right direction to a subject matter expert or those who can guide them with respect to their ethical use of data. So, for organizations that want to establish a data culture, how do they go about doing this work? Using the principles laid out in your book.

Saul Alinsky: (07:51)
Diving into the art of power analysis is a bit like playing the world's most strategic game of who's who, but instead of guessing who has a beard or wears glasses, you're pinpointing who holds the reins in the decision-making rodeo, and who's just there for the ride. It's a crucial step, because knowing who to talk to is half the battle. The other half is convincing them you're worth listening to, and that's where your charm, wit, and a hefty dose of strategic thinking come into play. Imagine the power structures within any group or society as a complex web of social media connections, but instead of following for cute cat videos or envy-inducing vacation snaps, you're mapping out the VIP list for your very own change-making party. You need to know who's who in the zoo, who's the lion king of the jungle, who's the wise owl in the tree, and who's just monkeying around. Once you know the influencers, you can identify who shares similar goals, and begin networking and building alliances to strengthen the collective influence to drive change.

Saul Alinsky: (08:53)
This can inform the movement on the sources of economic and cultural power to influence your strategic choices. To pull this off, you've got to be part detective, part diplomat, and part data analyst. Understanding the power dynamics at play requires keen observation, active listening, and the ability to read between the lines of organizational charts and social cues. It's about knowing not just who makes the decisions, but how they like their coffee. Finally, your communication strategy is your pièce de résistance, the crowning jewel of your campaign. It's not just about broadcasting your message, it's about tailoring it to resonate with your audience, whether that means memes, manifestos, or meticulously crafted emails that toe the line between persuasive and pestering. In the end, the success of your mission hinges on your ability to play the game with savvy and strategy. Because let's face it, changing minds and influencing power structures can sometimes feel like herding cats; frustrating, unpredictable, but ultimately rewarding when you finally get them all moving in the same direction.

Navigating corporate satire: The delicate art of provoking with humor

Satyen Sangani: (09:55)
You've hit the nail on the head. You've connect the principle of power analysis with building a data culture. It's all about spurring a movement and affecting cultural change. Now, on to the slightly trickier terrain of ridicule in the corporate sphere. You're absolutely right that unleashing ridicule in the office is akin to juggling flaming torches at a gas station. Technically possible, but maybe inadvisable unless you're aiming for a spectacularly short career. Is there a way that you can spin this principle to be more effective for corporate leaders?

Saul Alinsky: (10:24)
The fine art of wielding ridicule and satire in the battlefield of change. Delicate tools that when used with the finesse of a seasoned comedian can slice through the thickest of corporate red tapes or the densest of bureaucratic jungles. If you're suggesting that these tactics might alienate more people than persuade, let me challenge that a bit. One of the rules from my book is ridicule is man's most potent weapon. For listeners of this podcast, that's less about embarrassing colleagues and more about challenging the status quo. Good agents of change want to provoke engagement and stimulate discussion. By employing provocative tactics, organizers can draw attention to the issues at hand and encourage individuals to think critically about the status quo. In a professional setting, that's simply asking questions like, why are we doing it this way? And what is the opportunity cost of maintaining the status quo? It might be uncomfortable momentarily for those invested in or benefiting from the legacy processes, but those are far from inappropriate questions. In fact, I'd say they were required questions in a for-profit setting.

Saul Alinsky: (11:37)
Humor and satire, when deployed with the precision of a master strategist, can indeed rally the troops, shine a light on the absurdities of the status quo and perhaps even get a chuckle or two along the way. It's about crafting a message that sticks, like that catchy jingle from a commercial that you can't get out of your head, except this time it's about leveraging change, not selling you something you probably don't need. Navigating the corporate landscape with satire as your compass requires the agility of a cat, ready to pounce, but also poised to retract those claws and purr when needed. It's a balancing act, knowing when to push the envelope and when to seal it back up and mail it with a polite note attached. After all, the goal is to inspire change not incite a rebellion, unless of course, that's on the agenda. So, to the critics, I say lighten up. A little laughter can illuminate the path to change, making the journey less about confrontation and more about collaboration. And to the agents of change, read the room, tailor your tactics and remember sometimes the best way to disarm is with a smile, a well-placed joke and the courage to ask, why not?

Empowering teams: Upskilling organizational agility

Satyen Sangani: (12:46)
Okay, that's understandable. You want to challenge the institutional thinking and the red tape that bogs an organization down. I get that. It might be uncomfortable sometimes, but it's necessary for organizational and cultural growth. I try to challenge my team constantly, and I encourage them to challenge me and my reasoning too. It's not to undermine authority or cause embarrassment, but to ensure that we've all contemplated all of the ifs or the ands or the buts of the situation. So, let's drill down a little further. What advice from your book is relevant for those building a data culture?

Saul Alinsky: (13:15)
The sage advice of never go outside the expertise of your people. For data leaders, this is akin to saying don't send your vegetarians to a barbecue competition. It's all about playing to your strengths, recognizing that your team's prowess lies within their current skill set, and then arming them with the data equivalent of a culinary school education sans the fancy knife skills. Unless of course, you're slicing through big data. Imagine your team as a band of intrepid adventurers, each with their own unique set of skills. You wouldn't ask the bard to arm-wrestle a troll, just like you wouldn't task your analytics expert with, well, anything involving manual labor. The key here is to ensure that every team member becomes a data wizard in their own right, equipped with the magical spells of SQL queries, Python scripts, and the arcane arts of data visualization.

Saul Alinsky: (14:07)
By investing in data training and upskilling programs, you're essentially upgrading your team's armor and weaponry in the epic quest against the forces of ignorance and inefficiency. It's like giving them all a subscription to the data gym, a place where brain muscles flex, pivot tables are lifted with ease, and data models are run on treadmills. And let's not forget the motivational aspect. Nothing says, "I believe in you," quite like providing the resources for growth.

Democratizing data and crafting a culture of insight and empowerment

Satyen Sangani: (14:35)
Yes. Empowering employees to become data literate and capable within their roles is a crux of data culture. You want your people to be able to use data wisely, responsibly and appropriately, and you want that expertise, power and ability to be democratized and shared across the organization.

Saul Alinsky: (14:50)
Absolutely. In the grand theater of data and technology, this rule about distributing power, which means ensuring power doesn't get hoarded is like making sure everyone at the dinner table gets a slice of the pie. In this digital renaissance, where data is king and queen and possibly the entire court, understanding the intricacies of power dynamics isn't just smart, it's critical. Empowering the grassroots level in this context means giving everyone a voice. Not just the data scientists or the data engineers who speak in binary, it's about creating a symphony from the cacophony of voices, where the database manager's base harmonizes with the sales team's soprano. By fostering connections between these diverse perspectives, you're essentially hosting the world's most inclusive block party, where insights are the main dish and collaboration is the theme. This democratic approach to data-driven decision-making ensures that the power of data doesn't become the exclusive playground of a select few. Instead, it's a community garden where everyone can plant their questions and harvest insights. So yes, in this rapidly advancing age we're not just technology users, but participants in a grand experiment of digital democracy. By applying the principles of community organizing to data, we're not just making decisions, we're crafting a narrative of empowerment, one data point at a time.

How to successfully blend analytics with empathy for data-driven change

Satyen Sangani: (16:16)
Those are great rules, and I agree they apply to any corporate change management initiative. Interestingly, in my decades in the corporate world, no consultant or project leader ever equated change management with community building. It's an interesting analogy, and the more we dig into your book the more it makes sense, especially for data-related initiatives.

Saul Alinsky: (16:33)
Indeed, blending analytical skills with empathy in the realm of technology and data is a bit like being a gourmet chef in a kitchen full of ingredients from around the world. You've got your analytical skills sharp as a chef's knife, ready to slice and dice through data, while your empathy is the secret sauce that makes the final dish palatable to everyone at the table. From the spice loving thrill seeker, to the individual whose idea of adventurous eating is adding pepper to their mashed potatoes. Although the rules in my book may require some adaptation and creative application in a business context, they can serve as guiding principles for organizations seeking to leverage data effectively, instill a data-driven culture, and maximize the value of their data assets.

The timeless role of data in driving social change

Satyen Sangani: (17:17)
When you were alive and organizing, were there any notable instances where data and analytics such as they were available, played a role?

Saul Alinsky: (17:25)
[laughter] Indeed. It's like saying my organizing days were more abacus and less artificial intelligence, more carrier pigeon than cloud computing. Yet, despite the lack of flashy gadgets and the internet, data and information were still the unsung heroes of the day. I mentioned the five principles earlier, with power analysis as the first. To understand the power dynamics of a community, you have to understand that community. Where do they work? What are their political leanings? How much do they earn? How do they vote? Who do they respect? That's all data. And it may have been on ink and paper in my heyday, but it was still data that we analyzed and learned from. For instance, we gathered data on various aspects of the community such as demographics, social and economic conditions, local resources, and power structures. Data also allowed us to form alliances and build coalitions with like-minded organizations and individuals.

Satyen Sangani: (18:21)
That makes sense, because sharing data on goals, challenges, and resources helps foster collaboration and collective action. And naturally, you wanted to measure the progress and impact of your efforts.

Saul Alinsky: (18:33)
Absolutely. Back in the day, our data collection was more detective work with a notebook than digital dashboards and analytics. We'd gather information with the finesse of a gossip columnist, collecting anecdotes, testimonies and the kind of qualitative feedback that could only be whispered over a fence or shared at the local restaurant. But I have heard about modern grassroots organizations like 350.org that use data to track environmental changes, mobilize supporters for climate change initiatives, and plan strategic actions based on geographic and demographic data. And no current political organization, national or local, would survive without access to trusted data. So yes, while I might have missed the digital boat by a few decades, seeing the torch of change carried forward with such innovative and data-driven zeal is heartening.

Challenging assumptions and unveiling hidden truths

Satyen Sangani: (19:27)
You know, I'm always amazed by the ways that data can challenge our assumptions. During your days of organizing, were there any instances where the data you collected challenged the status quo and the assumptions of the day?

Saul Alinsky: (19:39)
Oh, absolutely. It turns out data has a bit of a superhero complex, swooping in to reveal the hidden stories and experiences that the dominant narratives tried to shove in the back of the closet, along with those embarrassing high school yearbook photos. Who knew that numbers and stats had the power to don capes and challenge the big bad villains of inequity and bias? In our adventures, we discovered that data could be as revealing as accidentally turning on the front-facing camera on your phone. Suddenly, there we were uncovering stark inequities in education and healthcare that were as obvious as a mismatched pair of socks, but had somehow flown under the radar of mainstream attention. By gathering data from those on the margins, we essentially gave them a megaphone. This was crucial when it came to misconceptions about crime and poverty. By collecting data on crime rates and comparing them to poverty levels, we could challenge the assumption that poverty was directly linked to criminal behavior. These insights helped to shift the narrative and advocate for more comprehensive solutions. Through data, we managed to not just whisper but shout from the rooftops, hey, these policies might need a second look. Presenting data that challenged prevailing assumptions created a sense of urgency and demonstrated the need for change.

How to unlock societal transformation with data and analytics

Satyen Sangani: (20:54)
I'm not sure if you've been keeping up with the events and society since your death. It probably is the case that there's a serious lack of WiFi where you're at or maybe not. But either way, do you see any opportunities in the world where we need to apply more data and analytics for change, considering the technology and the tools that we now have available?

Saul Alinsky: (21:12)
Absolutely. With today's tech, data and analytics are like the Swiss Army knives of societal transformation. They're not just tools. They're multifunctional marvels ready to tackle everything from deciphering the enigma of social and economic inequalities to plotting the course for a greener planet. Imagine smart cities where traffic jams are as outdated as dial-up internet. Thanks to data-driven urban planning, we could see a world where getting stuck in traffic is a tale we tell our grandkids to scare them, right alongside horror stories of living before WiFi. When it comes to public health and criminal justice reform, data and analytics are ready to step in like a detective duo, solving mysteries and righting wrongs, untangling complex societal issues with data visualizations and predictive models. On the global stage, data analytics and humanitarian efforts is akin to having a crystal ball. It's not about predicting the future, but about making informed, timely decisions that can save lives. The possibilities are indeed limitless. With data and analytics, we're not just changing the game, we're rewriting the rules and designing a better playbook for humanity. Now, if we could only analyze our way to never losing socks in the dryer, we'd truly have conquered the final frontier.

Balancing principals, values, and actions in the data age

Satyen Sangani: (22:30)
Before we sign off, I wanted to loop back around to some of the topics that I initially wanted to avoid. When you mentioned your five key principles, two of them felt decidedly alien to our discussion in the context of a business podcast. Those were that moral ends justify the means and you should use tactics of agitation. Related to the ethical considerations concerning the use of data, there's often this complex interplay between principles, values and consequences. In ethical discussions, a diverse set of perspectives and a commitment to understanding different viewpoints are crucial to navigating the complexities of moral decision-making. For example, it's a common challenge faced when confronting information released by a whistleblower. Did they commit a crime by divulging sensitive information or did they provide a public service by shining a light on a potential misdeed? So, for institutions and corporations that want to establish ethical data standards, how do they go about doing this work? We're hearing this more and more with the explosion of AI and generative AI technologies. Who decides what is moral? Who determines what is bias or the levels of bias? And furthermore, how can the concept of agitation be employed in a corporate setting?

Saul Alinsky: (23:32)
Let me tackle these individually. Morality and agitation. Diving into the quagmire of morality and decision-making is a bit like trying to agree on the best pizza topping in a room full of opinionated eaters. Everyone has their staunch beliefs. Some herald the virtues of pineapple, controversial I know, while others might consider anything beyond pepperoni a culinary blasphemy. Morality is inherently subjective and can vary among individuals, cultures, and societies. So, organizational leaders must consider the morals of their organization, industry, employees, home region or regions in which they are active and more. One way to navigate this is by providing frameworks for determining morality or to temper that language a bit, what is acceptable and unacceptable behavior for employees. Take the time. A ride-sharing company got fined for playing a bit too fast and loose with a Where's Waldo? Feature on customers sans permission. That data is clearly available via any smartphone app that has location services enabled, but it feels obviously unacceptable to use it to track individual people. Where it starts to move into the gray areas, companies need rules and policies to govern how data is used ethically. Humans can't always be trusted to make morally appropriate decisions.

Saul Alinsky: (24:47)
Unfortunately, even the higher-level managers might condone or look the other way when immoral behavior happens. Executives must engage in conversations that allow diverse perspectives to be heard so they can contribute to a more nuanced understanding of what is considered morally acceptable. Agitation is another sensitive subject. I see it as just a matter of articulation. Agitation is a marketing strategy. You're raising awareness, capturing attention and influencing perceptions. Marketers always try to create a sense of urgency by stirring emotions to prompt action. They highlight the pain points or challenges associated with a problem to evoke emotional responses from the audience. This could involve emphasizing the negative consequences of not addressing an issue or framing the problem in a way that resonates emotionally. Marketers might use storytelling, visual elements and messaging that simplifies complex issues to make them more accessible and engaging for the target audience. That helps the message resonate so that it stirs those core emotions that then prompt an action. Click this button, fill out this form, buy those shoes.

Saul Alinsky: (26:04)
While marketers typically use these techniques to promote products or services, the same principles can be applied to data culture, initiatives to generate awareness, mobilize support and influence stakeholder opinion. The effectiveness of these agitation tactics often lies in connecting with the audience emotionally and making the topic resonate with their values and interests.

The evolution of radical change

Satyen Sangani: (26:26)
This has been a really fascinating discussion. Any closing thoughts on the parallels between your rules for radicals and today's data radicals?

Saul Alinsky: (26:33)
The mention of community organizing might conjure up images of spirited picket lines and megaphone-led protests. But in reality, the charm of data really shakes things up. Data is like the unsung hero, turning our chance into charts and giving our cause that extra punch of legitimacy. Picture us armed with spreadsheets and pie charts, making a case for change that's as compelling as a detective drama climax. Data helped to bring evidence and credibility to our organizing efforts, enabling us to make a stronger case for change and mobilize communities around shared goals. Through the collection and presentation of data, we were able to shift narratives and challenge the prevailing power structures. Data is a critical tool for challenging conventional strategies and assumptions in the business context. Companies can leverage data to identify new market opportunities, optimize operations and better understand customer needs. Just as in grassroots organizing, data in business can shift narratives leading to innovation and disruption in traditional industries.

Saul Alinsky: (27:43)
It empowers businesses to make evidence-based decisions, fostering a culture of accountability and continuous improvement. By harnessing the power of data, businesses can more effectively navigate competitive landscapes, drive meaningful change, and be the radicals that change their organization or disrupt their industry.

Satyen Sangani: (28:04)
Thank you, Saul GP Alinsky, for joining us today, and thank you for listening. On a more serious note, we recognize that we're blurring the lines here and taking a whole bunch of editorial license relative to our regular format of first-party interviews. We recognize that this work has the opportunity to amaze, excite, and also potentially offend. While the latter isn't our intent, Oscar Wilde once said that life imitates art more than art imitates life. Whether that's true or not, our intention is to show the interplay of AI, data, and how we absorb information in a way that furthers your imagination in addition to your understanding. I'm Satyen Sangani, CEO of Alation. Data Radicals, keep learning and sharing until next season.

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Producer: (28:48)
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