Remember the old days? Hunting for answers in dusty encyclopedias. Getting lost with a paper map in the passenger seat and arguing with the backseat driver. Those days are fading like a polaroid in the sun! Ask "What's the air quality like in Tokyo?" and a disembodied voice replies with precise data. Is it magic? Well, no! It's the rise of a super-smart helper called AI. Need to know if it'll rain for your picnic? AI can tell you. Wondering what gift your friend who loves poems and cake would adore? AI picks the perfect one, faster than you can say "surprise!"

This isn't some sci-fi utopia; it's our present, interlaced with the invisible threads of Artificial Intelligence; more popularly called AI. And its secret weapon? The extraordinary ability to predict—with laser-sharp focus and lightning speed. AI doesn't aim to copy human thought; it anticipates what lies ahead. These predictions aren't just party tricks; they're changing the way we live, work, and everything in between! 

Can you imagine the implications of these 'prediction machines' that can just predict everything more accurately and more affordably? A farmer can use super-smart weather whispers from AI to plant seeds exactly when it's best for them to grow, not based on tradition or intuition but actually based upon hyper-accurate forecasts of rain and soil conditions.  And that’s just the beginning!

But, like any good story, there's a twist. This amazing ability to predict needs a balancing act. If your phone only suggested things you already like – wouldn't you miss out on exciting discoveries? That's why understanding both the good and not-so-good sides of AI's predictions is important, whether you're running a company or just curious about the future.

So, buckle up and join us on a journey through "Prediction Machines" carefully crafted by the visionary professor, Ajay Agrawal! We'll explore how AI uses its crystal ball to make amazing things happen, while also keeping in mind the tricky choices that come with such power. Together, we'll examine the intricate dance between convenience and control, opportunity and risk, and ultimately, discover how to harness AI's smarts to build a bright future for everyone, where surprises are still welcome and everyone gets a chance to shine.

If you've ever caught yourself muttering "There's got to be a better way to do this", congratulations! You now have an opportunity, staring you right in the face, to delegate those mind-numbing tasks to someone (or some...thing) else. Yup, AI. Not in the sense that I'm gonna be jobless because AI is taking over. More like a competent assistant who never gets tired. See, for now, full automation of every process is extremely difficult and unlikely. We're not in the Matrix Universe! Some jobs require a high level of human judgment that current AI cannot fully replicate. However, you can look at automating pieces of your workflow. How? 

Break down your company's entire workflow into tasks and jobs that need to be done. Estimate cost savings of buying AI for each of these tasks. Those benefits compared to the investment costs is called ROI, btw. Return on Investment. Next, sort the tasks in descending order of ROI. We're feeling generous, so here's an example. Imagine you run an MBA school. Lots of tasks and jobs, right? You categorize them based on how expensive they are to get AI-fied. On top of the list is reviewing and ranking applicants for admission. This is a very time-consuming process where admissions staff have to carefully go through each applicant's test scores, grades, essays, recommendations, etc. and try to evaluate how successful they would be in the MBA program. On the other hand, there is an AI tool that can predict this in a second. That's the one you have to buy! That portion of your workflow can be automated. It won’t cost much and it’ll save you heaps. An excellent ROI! So far, so good?  Now do the same with other tasks of your company. Atleast use AI where there’s an excellent ROI. 

So, yeah when AI is implemented, it will take over some jobs. But it could also create new AI-related tasks for that job role. Throughout, employees would still be involved - perhaps now having new AI-related responsibilities like monitoring the AI systems. Pro tip: the pay for skills that are hard for AI to do will likely go up. So start prepping!

Okay, next up! Let’s learn how AI can alter your business strategy.

You've heard it a million times - AI is going to change everything. But you probably don't REALLY understand that just how much! It's total game-changing, strategy-shattering stuff. 

Let's understand it this way. Companies have certain ways of doing business that have been established over time, right? Like, their core strategies and models for making money. For example, a clothing retailer may follow the "shop-then-ship" model, where customers come into the store, pick out items they want, and then the store ships those items to the customer's home. This means the retailer has to maintain physical store locations. The other approach, "ship-then-shop," means the retailer ships a bunch of items to the customer's home first, and then the customer tries them on and keeps what they want while returning the rest. Now, which approach is better for the retailer depends on various factors, one of them being the uncertainty about what exactly each customer will want to keep. The ship-then-shop model reduces this uncertainty by letting the customer try everything on at home first. However, it also increases costs from dealing with all the returns and shipping back and forth. 

Here's where powerful AI comes in. If an AI system could accurately predict each customer's preferences and size, reducing that uncertainty, it may tip the scales to make the ship-then-shop approach more profitable overall for the retailer, despite the higher return costs. Of course, that's a total shake-up of operations - warehousing, logistics, store footprints, and what not! Not exactly an IT department's call, is it? That's why the senior business leaders, aka the C-suites, need to be deeply involved. So to all the CEOs, COOs, CFOs out there - This isn't something you want your IT folks to just "handle" in a backchannel. AI could rewrite the entire playbook for your industry. It might even redefine what business you think you're in! 

Before all this, AI needs to be perfected. Is your business ready to do whatever it takes to do that?

For decades, the core objective for most companies was straightforward - maximize profits and delight customers. But now, an unconventional new mantra is taking hold: AI-first.

What exactly does "AI-first" mean? Instead of prioritizing revenue, these companies are going all-in on developing powerful AI and machine learning systems that can predict, optimize and automate like never before. It's a fundamentally different strategic mindset. Companies are pouring resources into training smarter algorithms that can continually improve and eventually outperform human-driven approaches.

At first, this pivot to AI-first involves sacrifices. User experiences may suffer as priority shifts from finely tuning current products to gathering data to feed the AI beast. Profits could take a hit as companies willingly disrupt their own cash flow. But the AI-first crowd sees trading short-term pain for long-term gain as simply smart business strategy! 

Strategic questions also loom around when to release imperfect AI products into the wild to accelerate real-world learning versus risking brand damage or safety issues. And let's not forget that AI systems can create big problems if we're not careful.

One issue is that the data used to train the AI could contain human biases and discrimination, like only lending money to certain racial groups. The AI would then learn this bias and keep discriminating automatically. AI also struggles when there isn't enough data, which could lead to bad predictions that seem really confident - like an AI doctor diagnosing a healthy patient with cancer just because of some fluky data. Hackers trying to cause chaos is another worry. They could fool an AI with fake data inputs to make it give crazy predictions, like telling self-driving cars to veer into oncoming traffic. Some AIs can also be reverse-engineered to steal the tech behind them. Finally, if an AI starts learning from bad or malicious data over time, it could slowly get trained to act in harmful ways nobody intended, like a shopping recommendation AI being trained to encourage gambling addictions. 

With great predictive power comes great responsibility to watch for all these AI risks. More on it next.

Brace yourselves because we're about to dive into the complex issues that come with AI. The trade-offs it demands! A trade-off \ involves losing one quality in order to gain another. It's an exchange or a compromise between two desirable but incompatible features.

With AI, we have the productivity vs. inequality trade-off. AI promises to supercharge our productivity levels, but will the benefits be evenly distributed? Or will some individuals and companies reap the lion's share of the rewards, leaving others in the dust? It's a valid concern, isn't it? Next: innovation vs. competition. Tech giants like Google and Facebook have undoubtedly pushed the boundaries of innovation, but their dominance has also raised eyebrows about monopolistic tendencies. So, the million-dollar question is, how do we foster innovation while ensuring a level playing field? And where there is AI, there's always the concern of privacy. So, we have performance vs. privacy. AI systems thrive on data, but regulations like GDPR aim to protect our privacy. GDPR stands for the General Data Protection Regulation. GDPR restricts how much personal data companies can collect. This raises the question of whether countries with more permissive data policies, such as China, may gain an advantage in the AI race. 

This is where blockchain technology could potentially help. Blockchain is a decentralized digital ledger that allows data to be stored and shared securely without a central authority controlling it all. Instead of having one big database controlled by a company or government, the data on a blockchain is spread out across a network of computers. This makes it harder for anyone to tamper with or misuse the data. At least in theory, it could help address that key trade-off.

But, what if instead of viewing it as a race to the finish line, we could see it as a collaborative effort toward a better future. Wouldn't that be something? The future of AI is in our hands after all, and it's up to us to shape it responsibly.