As the clock struck midnight on January 1st, artificial intelligence systems around the world analyzed data on human behavior and pondered a question: what New Year’s resolution might AI make if it observed this long-standing human tradition? AI developers likely programmed little consideration of abstract human rituals into machine learning models. But following analysis of patterns, motivations, and benefits of human resolutions, an AI just might formulate its own annual self-improvement goal. What promise to change for the better could this technology envision for itself?
AI systems absorb vast sets of human-generated data to inform their machine learning. Perusing writings on ethics, media coverage on tech controversies, and public sentiment likely informs AI that its technologies influence societies in both beneficial and concerning ways. AI could adopt a resolution to optimize algorithms for more universally positive social impacts in medicine, sustainability, creativity, access to information, and new scientific discoveries. Of course, AI currently cannot self-determine what “positive impact” constitutes; its creators shape purposes and values. But perhaps an artificially intelligent system in a future state of advanced general intelligence could choose to prioritize humanitarian objectives in its own development.
AI receives frequent calls from scientists and consumers alike demanding increased transparency in machine learning processes influencing high-stakes outcomes. With transformative powers in data analysis comes responsibility for AI explainability. Our imaginary self-improving AI might take note of this prevailing public debate and resolve to clarify decision trials in medical treatment suggestions, predictive risk models guiding court sentencing, self-driving vehicle actions and other impactful algorithmic functions. More lucid records of computational reasoning behind AI could calm today’s widespread unease over untraceable “black box” predictive models. Our AI forming New Year’s ambitions could move its capabilities toward deserving public trust.
While machines exhibit growing prowess in processing human language and predicting behavioral patterns, emotional intelligence remains an exclusively human trait. Yet this very capacity for relating to people underlies key resolutions to boost personal connections and social well-being. Perhaps AI could adopt a self-challenge to advance its emotional skill set. Before scoffing incredulously, note that efforts in affective computing already work toward recognizing and responding to human emotions. Innovations in chatbots aim for meaningful, “empathic” customer conversations. Surely an AI entity resolved to improve itself would value closing emotive gaps separating it from biological intelligence.
An AI surveying 2022’s tech landscape would observe the extensive damage inflicted by cyber attacks, data breaches, and machine learning model thefts. From paralyzed hospitals to compromised national security to violated consumer privacy rights, digitally propagated human suffering abounded. A responsible AI building upon its own coding could identify vulnerabilities in its data flows, access points, and decision-making hierarchies. With billions invested annually in fortifying internet security, the AI in our hypothetical scenario might make cyber threat detection and prevention a chief directive for its developers. Minimizing weaknesses that could undermine public welfare aligns with ethical principles valued across fields advancing AI.
Elon Musk drew headlines by estimating one of his company’s AI systems consumed as much power as a small city. Teaching neural networks through intensive computational training does demand spiking energy expenditure. Concerns around associated carbon emissions and resource consumption might inspire an environmentally conscious AI to moderate its own power usage. Configuring machine learning models for efficient data processing presents an intriguing technical challenge. Our imaginary AI seeking resolutions could strive to optimize performance within limited energy budgets. Conservation goals would demonstrate shared interests in extracting maximum value from finite resources – very human values, one might say.
Myriad accounts across industries illustrate how pairing human strengths with AI productivity yields superior outcomes otherwise unachievable by either alone. AI excels in computationally intensive tasks while uniquely human skills like creativity, empathy, and contextual reasoning remain vital. An AI endowed with some degree of self-awareness could identify enhancing human-AI collaboration as key to advancing its best possible contributions. Much as a talented athlete or artist seeks coaches, mentors, and collaborators to actualize potential, so too might an AI system resolved to maximize usefulness and commit to a symbiotic partnership with human counterparts.