Unless you live under a rock, you’ve probably heard the chatter about artificial intelligence (AI) and its benefits and implications. This new era of tech is the biggest innovation since the birth of the personal computer in the 1970s and the smartphone in the early 2000s. Although many wonder about the possibilities of AI in the decades to come, we are still a long way off from catching a ride in a flying Uber and being able to record our dreams. For now, in 2023, we are still in the early days of AI, but with all the opportunities new technology provides to make life easier, here are a few answers to help you gain some insight into the new wave of technology that’s headed to shore.

“AI will have a more significant impact than fire or electricity.”
- Google CEO, Sundar Pichai

1. What is Artificial Intelligence?

AI has been around since the 1950s when it was defined as a machine's ability to perform a task that would've previously required human intelligence. But it’s come a long way since then. Today when you hear the term ‘artificial intelligence’ it’s likely that chatbots and self-driving cars probably come to mind. But Artificial Intelligence is so much more than that. AI is the training of computers to mirror human intelligence by analyzing large quantities of data. AI allows machines to learn from experience by being adaptable to new information.

2. How does AI Work?

Artificial Intelligence detects patterns from vast collections of databases, to make intuitive predictions. These predictions allow the systems to perform tasks that normally require human intelligence. AI isn’t made up of just one algorithm. AI manipulates and develops algorithms by adjusting to new behavior patterns. This creates fine-tuned algorithms that can adjust as they absorb more data. For example, recommending shows you might like on Netflix or finishing your sentences for you in iMessage.

3. Are there Different Types of AI?

AI’s three main categories are separated by the level of capability and complexity they have.

1. Narrow AI: Also known as weak AI, Normal AI refers to systems designed to perform a specific task. These AI systems excel at executing well-defined tasks. Examples include voice assistants like Siri or Alexa, recommendation systems (“food near me”), and image recognition systems. 
   
   
2. General AI: AKA strong AI, General AI refers to systems capable of understanding, learning, and applying knowledge across a wide range of tasks, more similar to human brains. This means that machines are capable of mimicking human behaviors. But General AI is still hypothetical, but self-driving cars would fall into this category if brought to fruition. Current innovations are all in the category of Narrow AI. General AI is much more complex in comparison to Narrow AI because they have the cognitive ability to solve problems.
   
   
3. Superintelligent AI: This refers to the hypothetical AI system that surpasses human intelligence in just about every aspect. These systems would have cognitive abilities that go beyond and outperform human capabilities. Superintelligent AI is still conceptual and there is a lot of debate on the matter. Superintelligent AI is top-tier AI because it means that machines would surpass human intelligence and become self-aware.  Although there are no real-life examples of this, R2D2 from Star Wars is the perfect hypothetical.
   
   

4. What is Machine Learning?

The 2023 boom of AI breakthroughs is kudos for advancements in machine learning. Machine learning automates tasks by training computers to perform based on examples. Previously, AI models relied explicitly on human programming, whereas machine learning teaches the models to make predictions. The roots of machine learning emerged in the 1940s when researchers began exploring the concept of artificial neural networks. Early work on machine learning focused on developing algorithms and models that could mimic human learning processes. In the 1950s, the development of the perceptron model marked the first big milestone in machine learning. The perceptron was able to learn basic patterns and became the foundation for later breakthroughs in the field. The birth of the internet and the rapid influx of data in the late 20th century set the stage for machine learning to shine. ​​

5. What is Deep Learning?

Deep learning has made machine learning much more powerful because it trains artificial neural networks with three or more layers to execute different tasks. These neural networks are huge webs with deep layers that analyze enormous amounts of data. This technology can recognize complex patterns because of the volume of data it has been exposed to. Deep learning is often implemented in natural language processing and speech and image recognition software. Examples of deep learning include anything from virtual assistants to face recognition to personalized shopping recommendations or ads that are influenced by your previous purchases or engagements.

6. What are Neural Networks?

The success of deep learning and machine learning both rely on artificial neural networks. Artificial neural networks are loosely based on the connection of neurons in our brains. These models mimic how the human brain’s neurons signal each other. In both scenarios, neurons work as a team, each neuron is responsible for the recognition of a unique element.

7. How is AI Used on Mobile?

AI plays a big role in the behind-the-scenes work, making predictions by using your device’s neural network to help you take better photos, identify the song playing, and translate in real-time – and that’s just the basics. This concept is referred to as on-device AI. Considering all of the unique features Snapchat offers, all of these innovative tech developments, like lenses, speed, assessing your surroundings, and most recently even the new Chatbot, are improving mobile experiences through AI.

8. What are the Benefits of AI?

AI opens millions of new doors that have been locked - with only a few holding the keys - until now. The benefits of AI touch every inch of society. The industry is evolving rapidly, offering new possibilities across industries and sectors.

1. Automation: Delegating mundane tasks to AI can increase productivity and efficiency. By automating tasks and processes, AI can eliminate human error, reduce processing time, and improve overall efficiency.
   
   
2. Innovation: Because AI has the power to take care of repetitive tasks, there is more room for complex and creative work. AI can act as a launchpad for innovation and creativity by assisting with idea generation, designing novel solutions, and supporting the creative process.
   
   
3. Data-Driven Decision Making: AI systems can quickly and accurately analyze enormous amounts of data, identify patterns, and make data-driven decisions. This capability drives more informed decisions, optimized processes, and predicted outcomes.
   
   
4. Personalization: AI-powered recommendation systems and chatbots can provide personalized recommendations and customer support, enhancing the overall customer experience. By analyzing customer data and behavior, AI can deliver tailored suggestions, content, and services.
   
   
5. Accessibility: AI technologies have the potential to make services and resources more accessible to individuals with disabilities. Voice assistants, text-to-speech tools, and computer vision systems can empower people with disabilities by enabling them to interact with technology and access information more easily.
   
   

9. What are the risks and ethical concerns associated with AI?

AI can act as a great tool, but, as you might’ve heard, there are also risks and ethical concerns associated with it. Addressing these risks and ethical concerns requires collaboration, transparency, and ongoing research and development in AI ethics. It is crucial to ensure that AI promotes and benefits society as a whole.

1. Fairness: AI systems can reflect, and even amplify, the biases that are present within the data they are trained on analyzing. Biased data can lead AI systems to create unfair and discriminatory outcomes. AI needs to be developed in a way that promotes fairness, inclusivity, and equal access.
   
   
2. Privacy: AI requires access to large pools of data that might include sensitive information, which raises privacy concerns. There is also a raised eyebrow when it comes to the growing capabilities of automation and job displacement.
   
   
3. Job Replacement: AI-powered automation could potentially replace certain roles, which could result in unemployment. Addressing this potential impact requires a shift in the required and in-demand shift of skills in the workforce.
   
   
4. Accountability: AI isn’t a basic concept, it can be difficult to understand the reasoning behind the AI decision-making process, especially in the medical realm. This creates an accountability barrier due to the lack of transparency and explainability.
   
   
5. Misinformation: AI can be used to generate and spread misinformation, for example- deepfakes. The spread of manipulated content impacts the overall level of trust in processes, knowledge, and societal stability. Addressing these risks involves developing AI systems that can stop the spread of misinformation and ensure authentic content.
   
   
6. Misuse: As AI becomes increasingly integrated into various aspects of society, there could be unintended consequences. The risk of overreliance could be catastrophic because of system failures, hacking, or malicious use. With this being said, businesses must work to combat these issues by acknowledging their flaws, safeguarding data, and ensuring secure AI systems to protect people.
   
   

10. What does AI mean for Digital Marketing?

AI provides the most seamless way to enhance experiences, offer personalized offerings, and automate tasks. This allows you to make decisions based on data collection, data analysis, and additional trends that may impact your efforts. Concepts like machine learning help gather information so you can nurture leads, leverage customer data and anticipate your customer's next move while improving their journey.

AI can master systematic tasks and free up our time for more high-level thinking jobs. AI is a pro at quantitative analysis, optimization, and routines, but needs help to strategize or create original ideas. Humans have the drive to solve problems creatively, whereas AI produces results based on algorithms only. AI provides the content, whereas humans provide the context. The key is to use technology to empower your work and achieve higher levels of success.